tokens
list | ner_tags
list |
|---|---|
[
"Conditional",
"Random",
"Field",
"(CRF",
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"and",
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"neural",
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"have",
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"in",
"structured",
"prediction.",
"More",
"recently,",
"there",
"is",
"a",
"marriage",
"of",
"CRF",
"andrecurrent",
"neural",
"models,",
"so",
"that",
"we",
"can",
"gain",
"from",
"both",
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"densefeatures",
"and",
"globally",
"normalized",
"CRF",
"objective.",
"These",
"recurrent",
"neural",
"CRF",
"models",
"mainly",
"focus",
"on",
"encode",
"node",
"features",
"in",
"CRF",
"undirected",
"graphs.",
"However,edge",
"features",
"prove",
"important",
"to",
"CRF",
"in",
"structured",
"prediction.",
"In",
"this",
"work,",
"weintroduce",
"a",
"new",
"recurrent",
"neural",
"CRF",
"model,",
"which",
"learns",
"non-linear",
"edgefeatures,",
"and",
"thus",
"makes",
"non-linear",
"features",
"encoded",
"completely.",
"We",
"compare",
"ourmodel",
"with",
"different",
"neural",
"models",
"in",
"well-known",
"structured",
"prediction",
"tasks.Experiments",
"show",
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"our",
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"outperforms",
"state-of-the-art",
"methods",
"in",
"NPchunking,",
"shallow",
"parsing,",
"Chinese",
"word",
"segmentation",
"and",
"POS",
"tagging."
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[
"Classification",
"of",
"malignancy",
"for",
"breast",
"cancer",
"and",
"other",
"cancer",
"types",
"is",
"usually",
"tackled",
"as",
"an",
"object",
"detection",
"problem:",
"Individual",
"lesions",
"are",
"first",
"localized",
"and",
"then",
"classified",
"with",
"respect",
"to",
"malignancy.",
"However,",
"the",
"drawback",
"of",
"this",
"approach",
"is",
"that",
"abstract",
"features",
"incorporating",
"several",
"lesions",
"and",
"areas",
"that",
"are",
"not",
"labelled",
"as",
"a",
"lesion",
"but",
"contain",
"global",
"medically",
"relevant",
"information",
"are",
"thus",
"disregarded:",
"especially",
"for",
"dynamic",
"contrast-enhanced",
"breast",
"MRI,",
"criteria",
"such",
"as",
"background",
"parenchymal",
"enhancement",
"and",
"location",
"within",
"the",
"breast",
"are",
"important",
"for",
"diagnosis",
"and",
"cannot",
"be",
"captured",
"by",
"object",
"detection",
"approaches",
"properly.",
"In",
"this",
"work,",
"we",
"propose",
"a",
"3D",
"CNN",
"and",
"a",
"multi",
"scale",
"curriculum",
"learning",
"strategy",
"to",
"classify",
"malignancy",
"globally",
"based",
"on",
"an",
"MRI",
"of",
"the",
"whole",
"breast.",
"Thus,",
"the",
"global",
"context",
"of",
"the",
"whole",
"breast",
"rather",
"than",
"individual",
"lesions",
"is",
"taken",
"into",
"account.",
"Our",
"proposed",
"approach",
"does",
"not",
"rely",
"on",
"lesion",
"segmentations,",
"which",
"renders",
"the",
"annotation",
"of",
"training",
"data",
"much",
"more",
"effective",
"than",
"in",
"current",
"object",
"detection",
"approaches.",
"Achieving",
"an",
"AUROC",
"of",
"0.89,",
"we",
"compare",
"the",
"performance",
"of",
"our",
"approach",
"to",
"Mask",
"R-CNN",
"and",
"Retina",
"U-Net",
"as",
"well",
"as",
"a",
"radiologist.",
"Our",
"performance",
"is",
"on",
"par",
"with",
"approaches",
"that,",
"in",
"contrast",
"to",
"our",
"method,",
"rely",
"on",
"pixelwise",
"segmentations",
"of",
"lesions."
] |
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[
"The",
"field",
"of",
"intelligent",
"tutoring",
"systems",
"has",
"seen",
"many",
"successes",
"in",
"recent",
"years",
".",
"A",
"significant",
"remaining",
"challenge",
"is",
"the",
"automatic",
"creation",
"of",
"corpus-based",
"tutorial",
"dialogue",
"management",
"models",
".",
"This",
"paper",
"reports",
"on",
"early",
"work",
"toward",
"this",
"goal",
".",
"We",
"identify",
"tutorial",
"dialogue",
"modes",
"in",
"an",
"unsupervised",
"fashion",
"using",
"hidden",
"Markov",
"models",
"-LRB-",
"HMMs",
"-RRB-",
"trained",
"on",
"input",
"sequences",
"of",
"manually-labeled",
"dialogue",
"acts",
"and",
"adjacency",
"pairs",
".",
"The",
"two",
"best-fit",
"HMMs",
"are",
"presented",
"and",
"compared",
"with",
"respect",
"to",
"the",
"dialogue",
"structure",
"they",
"suggest",
";",
"we",
"also",
"discuss",
"potential",
"uses",
"of",
"the",
"methodology",
"for",
"future",
"work",
"."
] |
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[
"Large-scale",
"web-search",
"engines",
"are",
"generally",
"designed",
"for",
"linear",
"text",
".",
"The",
"linear",
"text",
"representation",
"is",
"suboptimal",
"for",
"audio",
"search",
",",
"where",
"accuracy",
"can",
"be",
"significantly",
"improved",
"if",
"the",
"search",
"includes",
"alternate",
"recognition",
"candidates",
",",
"commonly",
"represented",
"as",
"word",
"lattices",
".",
"This",
"paper",
"proposes",
"a",
"method",
"for",
"indexing",
"word",
"lattices",
"that",
"is",
"suitable",
"for",
"large-scale",
"web-search",
"engines",
",",
"requiring",
"only",
"limited",
"code",
"changes",
".",
"The",
"proposed",
"method",
",",
"called",
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"Merging",
"for",
"Indexing",
"-LRB-",
"TMI",
"-RRB-",
",",
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"converts",
"the",
"word",
"lattice",
"to",
"a",
"posterior-probability",
"representation",
"and",
"then",
"merges",
"word",
"hypotheses",
"with",
"similar",
"time",
"boundaries",
"to",
"reduce",
"the",
"index",
"size",
".",
"Four",
"alternative",
"approximations",
"are",
"presented",
",",
"which",
"differ",
"in",
"index",
"size",
"and",
"the",
"strictness",
"of",
"the",
"phrase-matching",
"constraints",
".",
"Results",
"are",
"presented",
"for",
"three",
"types",
"of",
"typical",
"web",
"audio",
"content",
",",
"podcasts",
",",
"video",
"clips",
",",
"and",
"online",
"lectures",
",",
"for",
"phrase",
"spotting",
"and",
"relevance",
"ranking",
".",
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"TMI",
"indexes",
"that",
"are",
"only",
"five",
"times",
"larger",
"than",
"corresponding",
"lineartext",
"indexes",
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"phrase",
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"searching",
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"transcripts",
"by",
"25-35",
"%",
",",
"and",
"relevance",
"ranking",
"by",
"14",
"%",
",",
"at",
"only",
"a",
"small",
"loss",
"compared",
"to",
"unindexed",
"lattice",
"search",
"."
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[
"Missing",
"data",
"are",
"unavoidable",
"in",
"wireless",
"sensor",
"networks,",
"due",
"to",
"issues",
"such",
"as",
"network",
"communication",
"outage,",
"sensor",
"maintenance",
"or",
"failure,",
"etc.",
"Although",
"a",
"plethora",
"of",
"methods",
"have",
"been",
"proposed",
"for",
"imputing",
"sensor",
"data,",
"limitations",
"still",
"exist.",
"Firstly,",
"most",
"methods",
"give",
"poor",
"estimates",
"when",
"a",
"consecutive",
"number",
"of",
"data",
"are",
"missing.",
"Secondly,",
"some",
"methods",
"reconstruct",
"missing",
"data",
"based",
"on",
"other",
"parameters",
"monitored",
"simultaneously.",
"When",
"all",
"the",
"data",
"are",
"missing,",
"these",
"methods",
"are",
"no",
"longer",
"effective.",
"Thirdly,",
"the",
"performance",
"of",
"deep",
"learning",
"methods",
"relies",
"highly",
"on",
"a",
"massive",
"number",
"of",
"training",
"data.",
"Moreover",
"in",
"many",
"scenarios,",
"it",
"is",
"difficult",
"to",
"obtain",
"large",
"volumes",
"of",
"data",
"from",
"wireless",
"sensor",
"networks.",
"Hence,",
"we",
"propose",
"a",
"new",
"sequence-to-sequence",
"imputation",
"model",
"(SSIM",
")",
"for",
"recovering",
"missing",
"data",
"in",
"wireless",
"sensor",
"networks.",
"The",
"SSIM",
"uses",
"the",
"state-of-the-art",
"sequence-to-sequence",
"deep",
"learning",
"architecture,",
"and",
"the",
"Long",
"Short",
"Term",
"Memory",
"Network",
"is",
"chosen",
"to",
"utilize",
"both",
"the",
"past",
"and",
"future",
"information",
"for",
"a",
"given",
"time.",
"Moreover,",
"a",
"variable-length",
"sliding",
"window",
"algorithm",
"is",
"developed",
"to",
"generate",
"a",
"large",
"number",
"of",
"training",
"samples",
"so",
"the",
"SSIM",
"can",
"be",
"trained",
"with",
"small",
"data",
"sets.",
"We",
"evaluate",
"the",
"SSIM",
"by",
"using",
"real-world",
"time",
"series",
"data",
"from",
"a",
"water",
"quality",
"monitoring",
"network.",
"Compared",
"to",
"methods",
"like",
"ARIMA,",
"Seasonal",
"ARIMA,",
"Matrix",
"Factorization,",
"Multivariate",
"Imputation",
"by",
"Chained",
"Equations",
"and",
"Expectation",
"Maximization,",
"the",
"proposed",
"SSIM",
"achieves",
"up",
"to",
"69.2%,",
"70.3%,",
"98.30%",
"and",
"76%",
"improvements",
"in",
"terms",
"of",
"the",
"RMSE,",
"MAE,",
"MAPE",
"and",
"SMAPE",
"respectively,",
"when",
"recovering",
"missing",
"data",
"sequences",
"of",
"three",
"different",
"lengths.",
"The",
"SSIM",
"is",
"therefore",
"a",
"promising",
"approach",
"for",
"data",
"quality",
"control",
"in",
"wireless",
"sensor",
"networks."
] |
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"Chat,",
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")",
"based",
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"Chat",
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"based",
"rerank",
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"industrial",
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"neural",
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"content",
"understanding,",
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"coding",
"algorithms",
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"traditional",
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"this",
"paper,",
"we",
"propose",
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"end-to-end",
"deep",
"neural",
"video",
"coding",
"framework",
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"spatial",
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"temporal",
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"pixels,",
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"motions",
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"multiscale",
"motion",
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"Sentence",
"embeddings",
"encode",
"sentences",
"in",
"fixed",
"dense",
"vectors",
"and",
"have",
"played",
"an",
"important",
"role",
"in",
"various",
"NLP",
"tasks",
"and",
"systems.",
"Methods",
"for",
"building",
"sentence",
"embeddings",
"include",
"unsupervised",
"learning",
"such",
"as",
"Quick-Thoughts",
"and",
"supervised",
"learning",
"such",
"as",
"InferSent.",
"With",
"the",
"success",
"of",
"pretrained",
"NLP",
"models,",
"recent",
"research",
"shows",
"that",
"fine-tuning",
"pretrained",
"BERT",
"on",
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"and",
"Multi-NLI",
"data",
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"state-of-the-art",
"sentence",
"embeddings,",
"outperforming",
"previous",
"sentence",
"embeddings",
"methods",
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"evaluation",
"benchmarks.",
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"this",
"paper,",
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"propose",
"a",
"new",
"method",
"to",
"build",
"sentence",
"embeddings",
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"doing",
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"contrastive",
"learning.",
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"method",
"fine-tunes",
"pretrained",
"BERT",
"on",
"SNLI",
"data,",
"incorporating",
"both",
"supervised",
"crossentropy",
"loss",
"and",
"supervised",
"contrastive",
"loss.",
"Compared",
"with",
"baseline",
"where",
"fine-tuning",
"is",
"only",
"done",
"with",
"supervised",
"cross-entropy",
"loss",
"similar",
"to",
"current",
"state-of-the-art",
"method",
"SBERT",
",",
"our",
"supervised",
"contrastive",
"method",
"improves",
"2.80%",
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"average",
"on",
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"Textual",
"Similarity",
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"benchmarks",
"and",
"1.05%",
"in",
"average",
"on",
"various",
"sentence",
"transfer",
"tasks."
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"the",
"most",
"deathful",
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"It",
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"spread",
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"on",
"the",
"off",
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"it",
"is",
"not",
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"cells,",
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"exposed",
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"The",
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"Furthermore,",
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"characterization",
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"malignant",
"growth",
"in",
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"a",
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"challenging",
"procedure.",
"It",
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"classified",
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"and",
"its",
"cell",
"type.",
"High",
"Precision",
"and",
"recall",
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"the",
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"lesions.",
"The",
"paper",
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"HAM-10000",
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"dermoscopy",
"images.",
"The",
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"cancer",
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"by",
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"the",
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"Neural",
"Network.",
"The",
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"methodology",
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"learning",
"model.",
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"taken,",
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"resolution.",
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"image",
"count",
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"also",
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"techniques.",
"In",
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"end,",
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"method",
"is",
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"accuracy",
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"the",
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"further.",
"Our",
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"a",
"weighted",
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"Precision",
"of",
"0.88,",
"a",
"weighted",
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"0.74,",
"and",
"a",
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"f1-score",
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"0.77.",
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"applied",
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"yielded",
"an",
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"We",
"propose",
"a",
"novel",
"time",
"series",
"averaging",
"method",
"based",
"on",
"Dynamic",
"Time",
"Warping",
"(DTW",
").",
"In",
"contrast",
"to",
"previous",
"methods,",
"our",
"algorithm",
"preserves",
"durational",
"information",
"and",
"the",
"distinctive",
"durational",
"features",
"of",
"the",
"sequences",
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"to",
"a",
"simple",
"conversion",
"of",
"the",
"output",
"of",
"DTW",
"into",
"a",
"time",
"sequence",
"and",
"an",
"innovative",
"iterative",
"averaging",
"process.",
"We",
"show",
"that",
"it",
"accurately",
"estimates",
"the",
"ground",
"truth",
"mean",
"sequences",
"and",
"mean",
"temporal",
"location",
"of",
"landmarks",
"in",
"synthetic",
"and",
"real-world",
"datasets",
"and",
"outperforms",
"state-of-the-art",
"methods."
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"We",
"consider",
"class",
"incremental",
"learning",
"(CIL)",
"problem,",
"in",
"which",
"a",
"learning",
"agent",
"continuously",
"learns",
"new",
"classes",
"from",
"incrementally",
"arriving",
"training",
"data",
"batches",
"and",
"aims",
"to",
"predict",
"well",
"on",
"all",
"the",
"classes",
"learned",
"so",
"far.",
"The",
"main",
"challenge",
"of",
"the",
"problem",
"is",
"the",
"catastrophic",
"forgetting,",
"and",
"for",
"the",
"exemplar-memory",
"based",
"CIL",
"methods,",
"it",
"is",
"generally",
"known",
"that",
"the",
"forgetting",
"is",
"commonly",
"caused",
"by",
"the",
"prediction",
"score",
"bias",
"that",
"is",
"injected",
"due",
"to",
"the",
"data",
"imbalance",
"between",
"the",
"new",
"classes",
"and",
"the",
"old",
"classes",
"(in",
"the",
"exemplar-memory).",
"While",
"several",
"methods",
"have",
"been",
"proposed",
"to",
"correct",
"such",
"score",
"bias",
"by",
"some",
"additional",
"post-processing,",
"e.g.,",
"score",
"re-scaling",
"or",
"balanced",
"fine-tuning,",
"no",
"systematic",
"analysis",
"on",
"the",
"root",
"cause",
"of",
"such",
"bias",
"has",
"been",
"done.",
"To",
"that",
"end,",
"we",
"analyze",
"that",
"computing",
"the",
"softmax",
"probabilities",
"by",
"combining",
"the",
"output",
"scores",
"for",
"all",
"old",
"and",
"new",
"classes",
"could",
"be",
"the",
"main",
"source",
"of",
"the",
"bias",
"and",
"propose",
"a",
"new",
"CIL",
"method,",
"Separated",
"Softmax",
"for",
"Incremental",
"Learning",
"(SS-IL).",
"Our",
"SS-IL",
"consists",
"of",
"separated",
"softmax",
"(SS)",
"output",
"layer",
"and",
"ratio-preserving",
"(RP)",
"mini-batches",
"combined",
"with",
"task-wise",
"knowledge",
"distillation",
"(TKD),",
"and",
"through",
"extensive",
"experimental",
"results,",
"we",
"show",
"our",
"SS-IL",
"achieves",
"very",
"strong",
"state-of-the-art",
"accuracy",
"on",
"several",
"large-scale",
"benchmarks.",
"We",
"also",
"show",
"SS-IL",
"makes",
"much",
"more",
"balanced",
"prediction,",
"without",
"any",
"additional",
"post-processing",
"steps",
"as",
"is",
"done",
"in",
"other",
"baselines."
] |
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[
"Hippocampus",
"segmentation",
"plays",
"a",
"key",
"role",
"in",
"diagnosing",
"various",
"brain",
"disorders",
"such",
"as",
"Alzheimer's",
"disease,",
"epilepsy,",
"multiple",
"sclerosis,",
"cancer,",
"depression",
"and",
"others.",
"Nowadays,",
"segmentation",
"is",
"still",
"mainly",
"performed",
"manually",
"by",
"specialists.",
"Segmentation",
"done",
"by",
"experts",
"is",
"considered",
"to",
"be",
"a",
"gold-standard",
"when",
"evaluating",
"automated",
"methods,",
"buts",
"it",
"is",
"a",
"time",
"consuming",
"and",
"arduos",
"task,",
"requiring",
"specialized",
"personnel.",
"In",
"recent",
"years,",
"efforts",
"have",
"been",
"made",
"to",
"achieve",
"reliable",
"automated",
"segmentation.",
"For",
"years",
"the",
"best",
"performing",
"authomatic",
"methods",
"were",
"multi",
"atlas",
"based",
"with",
"around",
"80-85%",
"Dice",
"coefficient",
"and",
"very",
"time",
"consuming,",
"but",
"machine",
"learning",
"methods",
"are",
"recently",
"rising",
"with",
"promising",
"time",
"and",
"accuracy",
"performance.",
"A",
"method",
"for",
"volumetric",
"hippocampus",
"segmentation",
"is",
"presented,",
"based",
"on",
"the",
"consensus",
"of",
"tri-planar",
"U-Net",
"inspired",
"fully",
"convolutional",
"networks",
"(FCNNs),",
"with",
"some",
"modifications,",
"including",
"residual",
"connections,",
"VGG",
"weight",
"transfers,",
"batch",
"normalization",
"and",
"a",
"patch",
"extraction",
"technique",
"employing",
"data",
"from",
"neighbor",
"patches.",
"A",
"study",
"on",
"the",
"impact",
"of",
"our",
"modifications",
"to",
"the",
"classical",
"U-Net",
"architecture",
"was",
"performed.",
"Our",
"method",
"achieves",
"cutting",
"edge",
"performance",
"in",
"our",
"dataset,",
"with",
"around",
"96%",
"volumetric",
"Dice",
"accuracy",
"in",
"our",
"test",
"data.",
"In",
"a",
"public",
"validation",
"dataset,",
"HARP,",
"we",
"achieve",
"87.48%",
"DICE.",
"GPU",
"execution",
"time",
"is",
"in",
"the",
"order",
"of",
"seconds",
"per",
"volume,",
"and",
"source",
"code",
"is",
"publicly",
"available.",
"Also,",
"masks",
"are",
"shown",
"to",
"be",
"similar",
"to",
"other",
"recent",
"state-of-the-art",
"hippocampus",
"segmentation",
"methods",
"in",
"a",
"third",
"dataset,",
"without",
"manual",
"annotations."
] |
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[
"Active",
"Learning",
"for",
"discriminative",
"models",
"has",
"largely",
"been",
"studied",
"with",
"the",
"focus",
"on",
"individual",
"samples,",
"with",
"less",
"emphasis",
"on",
"how",
"classes",
"are",
"distributed",
"or",
"which",
"classes",
"are",
"hard",
"to",
"deal",
"with.",
"In",
"this",
"work,",
"we",
"show",
"that",
"this",
"is",
"harmful.",
"We",
"propose",
"a",
"method",
"based",
"on",
"the",
"Bayes'",
"rule,",
"that",
"can",
"naturally",
"incorporate",
"class",
"imbalance",
"into",
"the",
"Active",
"Learning",
"framework.",
"We",
"derive",
"that",
"three",
"terms",
"should",
"be",
"considered",
"together",
"when",
"estimating",
"the",
"probability",
"of",
"a",
"classifier",
"making",
"a",
"mistake",
"for",
"a",
"given",
"sample;",
"i)",
"probability",
"of",
"mislabelling",
"a",
"class,",
"ii)",
"likelihood",
"of",
"the",
"data",
"given",
"a",
"predicted",
"class,",
"and",
"iii)",
"the",
"prior",
"probability",
"on",
"the",
"abundance",
"of",
"a",
"predicted",
"class.",
"Implementing",
"these",
"terms",
"requires",
"a",
"generative",
"model",
"and",
"an",
"intractable",
"likelihood",
"estimation.",
"Therefore,",
"we",
"train",
"a",
"Variational",
"Auto",
"Encoder",
"(VAE",
")",
"for",
"this",
"purpose.",
"To",
"further",
"tie",
"the",
"VAE",
"with",
"the",
"classifier",
"and",
"facilitate",
"VAE",
"training,",
"we",
"use",
"the",
"classifiers'",
"deep",
"feature",
"representations",
"as",
"input",
"to",
"the",
"VAE",
".",
"By",
"considering",
"all",
"three",
"probabilities,",
"among",
"them",
"especially",
"the",
"data",
"imbalance,",
"we",
"can",
"substantially",
"improve",
"the",
"potential",
"of",
"existing",
"methods",
"under",
"limited",
"data",
"budget.",
"We",
"show",
"that",
"our",
"method",
"can",
"be",
"applied",
"to",
"classification",
"tasks",
"on",
"multiple",
"different",
"datasets",
"--",
"including",
"one",
"that",
"is",
"a",
"real-world",
"dataset",
"with",
"heavy",
"data",
"imbalance",
"--",
"significantly",
"outperforming",
"the",
"state",
"of",
"the",
"art."
] |
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[
"Word",
"Embeddings",
"are",
"used",
"widely",
"in",
"multiple",
"Natural",
"Language",
"Processing",
"(NLP)",
"applications.",
"They",
"are",
"coordinates",
"associated",
"with",
"each",
"word",
"in",
"a",
"dictionary,",
"inferred",
"from",
"statistical",
"properties",
"of",
"these",
"words",
"in",
"a",
"large",
"corpus.",
"In",
"this",
"paper",
"we",
"introduce",
"the",
"notion",
"of",
"concept",
"as",
"a",
"list",
"of",
"words",
"that",
"have",
"shared",
"semantic",
"content.",
"We",
"use",
"this",
"notion",
"to",
"analyse",
"the",
"learnability",
"of",
"certain",
"concepts,",
"defined",
"as",
"the",
"capability",
"of",
"a",
"classifier",
"to",
"recognise",
"unseen",
"members",
"of",
"a",
"concept",
"after",
"training",
"on",
"a",
"random",
"subset",
"of",
"it.",
"We",
"first",
"use",
"this",
"method",
"to",
"measure",
"the",
"learnability",
"of",
"concepts",
"on",
"pretrained",
"word",
"embeddings.",
"We",
"then",
"develop",
"a",
"statistical",
"analysis",
"of",
"concept",
"learnability,",
"based",
"on",
"hypothesis",
"testing",
"and",
"ROC",
"curves,",
"in",
"order",
"to",
"compare",
"the",
"relative",
"merits",
"of",
"various",
"embedding",
"algorithms",
"using",
"a",
"fixed",
"corpora",
"and",
"hyper",
"parameters.",
"We",
"find",
"that",
"all",
"embedding",
"methods",
"capture",
"the",
"semantic",
"content",
"of",
"those",
"word",
"lists,",
"but",
"fastText",
"performs",
"better",
"than",
"the",
"others."
] |
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[
"Fully",
"unsupervised",
"pattern-based",
"methods",
"for",
"discovery",
"of",
"word",
"categories",
"have",
"been",
"proven",
"to",
"be",
"useful",
"in",
"several",
"languages",
".",
"The",
"majority",
"of",
"these",
"methods",
"rely",
"on",
"the",
"existence",
"of",
"function",
"words",
"as",
"separate",
"text",
"units",
".",
"However",
",",
"in",
"morphology-rich",
"languages",
",",
"in",
"particular",
"Semitic",
"languages",
"such",
"as",
"Hebrew",
"and",
"Arabic",
",",
"the",
"equivalents",
"of",
"such",
"function",
"words",
"are",
"usually",
"written",
"as",
"morphemes",
"attached",
"as",
"prefixes",
"to",
"other",
"words",
".",
"As",
"a",
"result",
",",
"they",
"are",
"missed",
"by",
"word-based",
"pattern",
"discovery",
"methods",
",",
"causing",
"many",
"useful",
"patterns",
"to",
"be",
"undetected",
"and",
"a",
"drastic",
"deterioration",
"in",
"performance",
".",
"To",
"enable",
"high",
"quality",
"lexical",
"category",
"acquisition",
",",
"we",
"propose",
"a",
"simple",
"unsupervised",
"word",
"segmentation",
"algorithm",
"that",
"separates",
"these",
"morphemes",
".",
"We",
"study",
"the",
"performance",
"of",
"the",
"algorithm",
"for",
"Hebrew",
"and",
"Arabic",
",",
"and",
"show",
"that",
"it",
"indeed",
"improves",
"a",
"state-of-art",
"unsupervised",
"concept",
"acquisition",
"algorithm",
"in",
"Hebrew",
"."
] |
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[
"In",
"this",
"paper,",
"we",
"tackle",
"a",
"problem",
"of",
"predicting",
"phenotypes",
"from",
"structuralconnectomes.",
"We",
"propose",
"that",
"normalized",
"Laplacian",
"spectra",
"can",
"capturestructural",
"properties",
"of",
"brain",
"networks,",
"and",
"hence",
"graph",
"spectral",
"distributionsare",
"useful",
"for",
"a",
"task",
"of",
"connectome-based",
"classification.",
"We",
"introduce",
"a",
"kernelthat",
"is",
"based",
"on",
"earth",
"mover's",
"distance",
"(EMD)",
"between",
"spectral",
"distributions",
"ofbrain",
"networks.",
"We",
"access",
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"classifier",
"with",
"the",
"proposedkernel",
"for",
"a",
"task",
"of",
"classification",
"of",
"autism",
"spectrum",
"disorder",
"versus",
"typicaldevelopment",
"based",
"on",
"a",
"publicly",
"available",
"dataset.",
"Classification",
"quality",
"(areaunder",
"the",
"ROC-curve)",
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"the",
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"kernel",
"on",
"spectraldistributions",
"is",
"0.71,",
"which",
"is",
"higher",
"than",
"that",
"based",
"on",
"simpler",
"graphembedding",
"methods."
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[
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"progress",
"of",
"deep",
"learning",
"fuels",
"end-to-end",
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"like",
"robotic",
"scenarios",
"still",
"suffers",
"from",
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"sample",
"efficiency.",
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"State",
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"to",
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"states.",
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"learned",
"separately,",
"which",
"is",
"prone",
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"problem,",
"we",
"present",
"a",
"new",
"algorithm",
"called",
"Policy",
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"SRL",
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"the",
"states",
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"to",
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"a",
"dynamic",
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"adjustment",
"mechanism",
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"that",
"both",
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"adapt",
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"introduce",
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"new",
"prior",
"called",
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"resemblance",
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"expert",
"demonstration",
"to",
"train",
"the",
"SRL",
"model.",
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"we",
"provide",
"a",
"real-time",
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"by",
"state",
"graph",
"to",
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"the",
"course",
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"learning.",
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"show",
"that",
"our",
"algorithm",
"outperforms",
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"baselines",
"and",
"decoupling",
"strategies",
"in",
"terms",
"of",
"sample",
"efficiency",
"and",
"final",
"rewards.",
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"our",
"model",
"can",
"efficiently",
"deal",
"with",
"tasks",
"in",
"high",
"dimensions",
"and",
"facilitate",
"training",
"real-life",
"robots",
"directly",
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"leverage",
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"encoder",
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"the",
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"and",
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"generator",
"to",
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"generator",
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"model.",
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"transfer",
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"encoder",
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"generator.",
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"faces,",
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"and",
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"35%",
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"quantitatively",
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"significantly",
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"I2I",
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"especially",
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"small",
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"first",
"to",
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"I2I",
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"for",
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"with",
"over",
"100",
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"sampling",
"efficiency.",
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"improves",
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"first",
"introduce",
"a",
"novel",
"profile-based",
"alignment",
"algorithm,",
"the",
"multiple",
"continuous",
"Signal",
"Alignment",
"algorithm",
"with",
"Gaussian",
"Process",
"Regression",
"profiles",
"(SA-GPR).",
"SA-GPR",
"addresses",
"the",
"limitations",
"of",
"currently",
"available",
"signal",
"alignment",
"methods",
"by",
"adopting",
"a",
"hybrid",
"of",
"the",
"particle",
"smoothing",
"and",
"Markov-chain",
"Monte",
"Carlo",
"(MCMC)",
"algorithms",
"to",
"align",
"signals,",
"and",
"by",
"applying",
"the",
"Gaussian",
"process",
"regression",
"to",
"construct",
"profiles",
"to",
"be",
"aligned",
"continuously.",
"SA-GPR",
"shares",
"all",
"the",
"strengths",
"of",
"the",
"existing",
"alignment",
"algorithms",
"that",
"depend",
"on",
"profiles",
"but",
"is",
"more",
"exact",
"in",
"the",
"sense",
"that",
"profiles",
"do",
"not",
"need",
"to",
"be",
"discretized",
"as",
"sequential",
"bins.",
"The",
"uncertainty",
"of",
"performance",
"over",
"the",
"resolution",
"of",
"such",
"bins",
"is",
"thereby",
"eliminated.",
"This",
"methodology",
"produces",
"alignments",
"that",
"are",
"consistent,",
"that",
"regularize",
"extreme",
"cases,",
"and",
"that",
"properly",
"reflect",
"the",
"inherent",
"uncertainty.",
"Then",
"we",
"extend",
"SA-GPR",
"to",
"a",
"specific",
"problem",
"in",
"the",
"field",
"of",
"paleoceanography",
"with",
"a",
"method",
"called",
"Bayesian",
"Inference",
"Gaussian",
"Process",
"Multiproxy",
"Alignment",
"of",
"Continuous",
"Signals",
"(BIGMACS).",
"The",
"goal",
"of",
"BIGMACS",
"is",
"to",
"infer",
"continuous",
"ages",
"for",
"ocean",
"sediment",
"cores",
"using",
"two",
"classes",
"of",
"age",
"proxies:",
"proxies",
"that",
"explicitly",
"return",
"calendar",
"ages",
"(e.g.,",
"radiocarbon)",
"and",
"those",
"used",
"to",
"synchronize",
"ages",
"in",
"multiple",
"marine",
"records",
"(e.g.,",
"an",
"oxygen",
"isotope",
"based",
"marine",
"proxy",
"known",
"as",
"benthic",
"${\\delta}^{18}{\\rm",
"O}$).",
"BIGMACS",
"integrates",
"these",
"two",
"proxies",
"by",
"iteratively",
"performing",
"two",
"steps:",
"profile",
"construction",
"from",
"benthic",
"${\\delta}^{18}{\\rm",
"O}$",
"age",
"models",
"and",
"alignment",
"of",
"each",
"core",
"to",
"the",
"profile",
"also",
"reflecting",
"radiocarbon",
"dates.",
"We",
"use",
"BIGMACS",
"to",
"construct",
"a",
"new",
"Deep",
"Northeastern",
"Atlantic",
"stack",
"(i.e.,",
"a",
"profile",
"from",
"a",
"particular",
"benthic",
"${\\delta}^{18}{\\rm",
"O}$",
"records)",
"of",
"five",
"ocean",
"sediment",
"cores.",
"We",
"conclude",
"by",
"constructing",
"multiproxy",
"age",
"models",
"for",
"two",
"additional",
"cores",
"from",
"the",
"same",
"region",
"by",
"aligning",
"them",
"to",
"the",
"stack."
] |
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[
"Generative",
"Adversarial",
"Networks",
"(GAN",
")",
"boast",
"impressive",
"capacity",
"to",
"generaterealistic",
"images.",
"However,",
"like",
"much",
"of",
"the",
"field",
"of",
"deep",
"learning,",
"theyrequire",
"an",
"inordinate",
"amount",
"of",
"data",
"to",
"produce",
"results,",
"thereby",
"limiting",
"theirusefulness",
"in",
"generating",
"novelty.",
"In",
"the",
"same",
"vein,",
"recent",
"advances",
"inmeta-learning",
"have",
"opened",
"the",
"door",
"to",
"many",
"few-shot",
"learning",
"applications.",
"Inthe",
"present",
"work,",
"we",
"propose",
"Few-shot",
"Image",
"Generation",
"using",
"Reptile",
"(FIGR),",
"aGAN",
"meta-trained",
"with",
"Reptile.",
"Our",
"model",
"successfully",
"generates",
"novel",
"images",
"onboth",
"MNIST",
"and",
"Omniglot",
"with",
"as",
"little",
"as",
"4",
"images",
"from",
"an",
"unseen",
"class.",
"Wefurther",
"contribute",
"FIGR-8,",
"a",
"new",
"dataset",
"for",
"few-shot",
"image",
"generation,",
"whichcontains",
"1,548,944",
"icons",
"categorized",
"in",
"over",
"18,409",
"classes.",
"Trained",
"on",
"FIGR-8,initial",
"results",
"show",
"that",
"our",
"model",
"can",
"generalize",
"to",
"more",
"advanced",
"concepts(such",
"as",
"bird",
"and",
"knife)",
"from",
"as",
"few",
"as",
"8",
"samples",
"from",
"a",
"previously",
"unseenclass",
"of",
"images",
"and",
"as",
"little",
"as",
"10",
"training",
"steps",
"through",
"those",
"8",
"images.",
"Thiswork",
"demonstrates",
"the",
"potential",
"of",
"training",
"a",
"GAN",
"for",
"few-shot",
"image",
"generationand",
"aims",
"to",
"set",
"a",
"new",
"benchmark",
"for",
"future",
"work",
"in",
"the",
"domain."
] |
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[
"Object",
"Detection",
"is",
"a",
"popular",
"field",
"of",
"research",
"for",
"recent",
"technologies.",
"In",
"recent",
"years,",
"profound",
"learning",
"performance",
"attracts",
"the",
"researchers",
"to",
"use",
"it",
"in",
"many",
"applications.",
"Number",
"plate",
"(NP)",
"detection",
"and",
"classification",
"is",
"analyzed",
"over",
"decades",
"however,",
"it",
"needs",
"approaches",
"which",
"are",
"more",
"precise",
"and",
"state,",
"language",
"and",
"design",
"independent",
"since",
"cars",
"are",
"now",
"moving",
"from",
"state",
"to",
"another",
"easily.",
"In",
"this",
"paperwe",
"suggest",
"a",
"new",
"strategy",
"to",
"detect",
"NP",
"and",
"comprehend",
"the",
"nation,",
"language",
"and",
"layout",
"of",
"NPs.",
"YOLOv2",
"sensor",
"with",
"ResNet",
"attribute",
"extractor",
"heart",
"is",
"proposed",
"for",
"NP",
"detection",
"and",
"a",
"brand",
"new",
"convolutional",
"neural",
"network",
"architecture",
"is",
"suggested",
"to",
"classify",
"NPs.",
"The",
"detector",
"achieves",
"average",
"precision",
"of",
"99.57%",
"and",
"country,",
"language",
"and",
"layout",
"classification",
"precision",
"of",
"99.33%.",
"The",
"results",
"outperforms",
"the",
"majority",
"of",
"the",
"previous",
"works",
"and",
"can",
"move",
"the",
"area",
"forward",
"toward",
"international",
"NP",
"detection",
"and",
"recognition."
] |
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[
"In",
"this",
"paper",
"we",
"propose",
"the",
"utterance-level",
"Permutation",
"Invariant",
"Training(uPIT",
")",
"technique.",
"uPIT",
"is",
"a",
"practically",
"applicable,",
"end-to-end,",
"deep",
"learningbased",
"solution",
"for",
"speaker",
"independent",
"multi-talker",
"speech",
"separation.Specifically,",
"uPIT",
"extends",
"the",
"recently",
"proposed",
"Permutation",
"Invariant",
"Training(PIT)",
"technique",
"with",
"an",
"utterance-level",
"cost",
"function,",
"hence",
"eliminating",
"theneed",
"for",
"solving",
"an",
"additional",
"permutation",
"problem",
"during",
"inference,",
"which",
"isotherwise",
"required",
"by",
"frame-level",
"PIT.",
"We",
"achieve",
"this",
"using",
"Recurrent",
"NeuralNetworks",
"(RNNs)",
"that,",
"during",
"training,",
"minimize",
"the",
"utterance-level",
"separationerror,",
"hence",
"forcing",
"separated",
"frames",
"belonging",
"to",
"the",
"same",
"speaker",
"to",
"bealigned",
"to",
"the",
"same",
"output",
"stream.",
"In",
"practice,",
"this",
"allows",
"RNNs,",
"trained",
"withuPIT",
",",
"to",
"separate",
"multi-talker",
"mixed",
"speech",
"without",
"any",
"prior",
"knowledge",
"ofsignal",
"duration,",
"number",
"of",
"speakers,",
"speaker",
"identity",
"or",
"gender.",
"We",
"evaluateduPIT",
"on",
"the",
"WSJ0",
"and",
"Danish",
"two-",
"and",
"three-talker",
"mixed-speech",
"separation",
"tasksand",
"found",
"that",
"uPIT",
"outperforms",
"techniques",
"based",
"on",
"Non-negative",
"MatrixFactorization",
"(NMF)",
"and",
"Computational",
"Auditory",
"Scene",
"Analysis",
"(CASA),",
"andcompares",
"favorably",
"with",
"Deep",
"Clustering",
"(DPCL)",
"and",
"the",
"Deep",
"Attractor",
"Network(DANet).",
"Furthermore,",
"we",
"found",
"that",
"models",
"trained",
"with",
"uPIT",
"generalize",
"well",
"tounseen",
"speakers",
"and",
"languages.",
"Finally,",
"we",
"found",
"that",
"a",
"single",
"model,",
"trainedwith",
"uPIT",
",",
"can",
"handle",
"both",
"two-speaker,",
"and",
"three-speaker",
"speech",
"mixtures."
] |
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[
"The",
"deep",
"Q-network",
"(DQN",
")",
"and",
"return-based",
"reinforcement",
"learning",
"are",
"two",
"promising",
"algorithms",
"proposed",
"in",
"recent",
"years.",
"DQN",
"brings",
"advances",
"to",
"complex",
"sequential",
"decision",
"problems,",
"while",
"return-based",
"algorithms",
"have",
"advantages",
"in",
"making",
"use",
"of",
"sample",
"trajectories.",
"In",
"this",
"paper,",
"we",
"propose",
"a",
"general",
"framework",
"to",
"combine",
"DQN",
"and",
"most",
"of",
"the",
"return-based",
"reinforcement",
"learning",
"algorithms,",
"named",
"R-DQN",
".",
"We",
"show",
"the",
"performance",
"of",
"traditional",
"DQN",
"can",
"be",
"improved",
"effectively",
"by",
"introducing",
"return-based",
"reinforcement",
"learning.",
"In",
"order",
"to",
"further",
"improve",
"the",
"R-DQN",
",",
"we",
"design",
"a",
"strategy",
"with",
"two",
"measurements",
"which",
"can",
"qualitatively",
"measure",
"the",
"policy",
"discrepancy.",
"Moreover,",
"we",
"give",
"the",
"two",
"measurements'",
"bounds",
"in",
"the",
"proposed",
"R-DQN",
"framework.",
"We",
"show",
"that",
"algorithms",
"with",
"our",
"strategy",
"can",
"accurately",
"express",
"the",
"trace",
"coefficient",
"and",
"achieve",
"a",
"better",
"approximation",
"to",
"return.",
"The",
"experiments,",
"conducted",
"on",
"several",
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"tasks",
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"library,",
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"the",
"algorithms",
"with",
"our",
"strategy",
"outperform",
"the",
"state-of-the-art",
"methods."
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"knowledge",
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"phrases",
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"then",
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"and",
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"e.",
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"to",
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"of",
"multi-words",
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"Acknowledgement",
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"this",
"work",
"was",
"carried",
"out",
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"project",
"EUII",
".",
"OTP",
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"ET-10",
"\\/",
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"the",
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"dataset,",
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"results",
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"optimally",
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"prior,",
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"epochs,",
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"the",
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"configurations",
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"then",
"show",
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"significantly",
"lower",
"precision",
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"last",
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"we",
"achieve",
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"memory",
"savings.",
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"test",
"our",
"findings",
"on",
"the",
"CIFAR10",
"and",
"ImageNet",
"datasets",
"using",
"the",
"VGG,",
"ResNet",
"and",
"GoogLeNet",
"architectures."
] |
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"Prognostics",
"and",
"Health",
"Management",
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"an",
"emerging",
"engineering",
"discipline",
"which",
"is",
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"with",
"the",
"analysis",
"and",
"prediction",
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"equipment",
"health",
"and",
"performance.",
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"challenges",
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"is",
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"predict",
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"equipment.",
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"recent",
"years,",
"solutions",
"for",
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"prediction",
"have",
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"from",
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"physical",
"models",
"to",
"the",
"use",
"of",
"machine",
"learning",
"algorithms",
"that",
"leverage",
"the",
"data",
"generated",
"by",
"the",
"equipment.",
"However,",
"failure",
"prediction",
"problems",
"pose",
"a",
"set",
"of",
"unique",
"challenges",
"that",
"make",
"direct",
"application",
"of",
"traditional",
"classification",
"and",
"prediction",
"algorithms",
"impractical.",
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"challenges",
"include",
"the",
"highly",
"imbalanced",
"training",
"data,",
"the",
"extremely",
"high",
"cost",
"of",
"collecting",
"more",
"failure",
"samples,",
"and",
"the",
"complexity",
"of",
"the",
"failure",
"patterns.",
"Traditional",
"oversampling",
"techniques",
"will",
"not",
"be",
"able",
"to",
"capture",
"such",
"complexity",
"and",
"accordingly",
"result",
"in",
"overfitting",
"the",
"training",
"data.",
"This",
"paper",
"addresses",
"these",
"challenges",
"by",
"proposing",
"a",
"novel",
"algorithm",
"for",
"failure",
"prediction",
"using",
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"Adversarial",
"Networks",
"(GAN",
"-FP).",
"GAN",
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"first",
"utilizes",
"two",
"GAN",
"networks",
"to",
"simultaneously",
"generate",
"training",
"samples",
"and",
"build",
"an",
"inference",
"network",
"that",
"can",
"be",
"used",
"to",
"predict",
"failures",
"for",
"new",
"samples.",
"GAN",
"#NAME?",
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"failure",
"and",
"non-failure",
"samples,",
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"initialize",
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"weights",
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"the",
"first",
"few",
"layers",
"of",
"the",
"inference",
"network.",
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"inference",
"network",
"is",
"then",
"tuned",
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"optimizing",
"a",
"weighted",
"loss",
"objective",
"using",
"only",
"real",
"failure",
"and",
"non-failure",
"samples.",
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"inference",
"network",
"is",
"further",
"tuned",
"using",
"a",
"second",
"GAN",
"whose",
"purpose",
"is",
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"guarantee",
"the",
"consistency",
"between",
"the",
"generated",
"samples",
"and",
"corresponding",
"labels.",
"GAN",
"#NAME?",
"can",
"be",
"used",
"for",
"other",
"imbalanced",
"classification",
"problems",
"as",
"well."
] |
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"This",
"paper",
"studies",
"the",
"effect",
"of",
"the",
"order",
"of",
"depth",
"of",
"mention",
"on",
"nested",
"named",
"entity",
"recognition",
"(NER",
")",
"models.",
"NER",
"is",
"an",
"essential",
"task",
"in",
"the",
"extraction",
"of",
"biomedical",
"information,",
"and",
"nested",
"entities",
"are",
"common",
"since",
"medical",
"concepts",
"can",
"assemble",
"to",
"form",
"larger",
"entities.",
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"NER",
"systems",
"only",
"predict",
"disjointed",
"entities.",
"Thus,",
"iterative",
"models",
"for",
"nested",
"NER",
"use",
"multiple",
"predictions",
"to",
"enumerate",
"all",
"entities,",
"imposing",
"a",
"predefined",
"order",
"from",
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"to",
"smallest",
"or",
"smallest",
"to",
"largest.",
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"design",
"an",
"order-agnostic",
"iterative",
"model",
"and",
"a",
"procedure",
"to",
"choose",
"a",
"custom",
"order",
"during",
"training",
"and",
"prediction.",
"To",
"accommodate",
"for",
"this",
"task,",
"we",
"propose",
"a",
"modification",
"of",
"the",
"Transformer",
"architecture",
"to",
"take",
"into",
"account",
"the",
"entities",
"predicted",
"in",
"the",
"previous",
"steps.",
"We",
"provide",
"a",
"set",
"of",
"experiments",
"to",
"study",
"the",
"model's",
"capabilities",
"and",
"the",
"effects",
"of",
"the",
"order",
"on",
"performance.",
"Finally,",
"we",
"show",
"that",
"the",
"smallest",
"to",
"largest",
"order",
"gives",
"the",
"best",
"results."
] |
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"Existing",
"image-to-image",
"translation",
"(I2IT)",
"methods",
"are",
"either",
"constrained",
"to",
"low-resolution",
"images",
"or",
"long",
"inference",
"time",
"due",
"to",
"their",
"heavy",
"computational",
"burden",
"on",
"the",
"convolution",
"of",
"high-resolution",
"feature",
"maps.",
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"this",
"paper,",
"we",
"focus",
"on",
"speeding-up",
"the",
"high-resolution",
"photorealistic",
"I2IT",
"tasks",
"based",
"on",
"closed-form",
"Laplacian",
"pyramid",
"decomposition",
"and",
"reconstruction.",
"Specifically,",
"we",
"reveal",
"that",
"the",
"attribute",
"transformations,",
"such",
"as",
"illumination",
"and",
"color",
"manipulation,",
"relate",
"more",
"to",
"the",
"low-frequency",
"component,",
"while",
"the",
"content",
"details",
"can",
"be",
"adaptively",
"refined",
"on",
"high-frequency",
"components.",
"We",
"consequently",
"propose",
"a",
"Laplacian",
"Pyramid",
"Translation",
"Network",
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"progressive",
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"refine",
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"high-frequency",
"ones.",
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"model",
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"most",
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"the",
"heavy",
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"consumed",
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"processing",
"high-resolution",
"feature",
"maps",
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"image",
"details.",
"Extensive",
"experimental",
"results",
"on",
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"tasks",
"demonstrate",
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"the",
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"method",
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"GPU",
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"performance",
"against",
"existing",
"methods.",
"Datasets",
"and",
"codes",
"are",
"available:",
"https://github.com/csjliang/LPTN."
] |
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[
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"learning",
"(CL)",
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"the",
"problem",
"of",
"learning",
"a",
"sequence",
"of",
"tasks,",
"one",
"at",
"a",
"time,",
"such",
"that",
"the",
"learning",
"of",
"each",
"new",
"task",
"does",
"not",
"lead",
"to",
"the",
"deterioration",
"in",
"performance",
"on",
"the",
"previously",
"seen",
"ones",
"while",
"exploiting",
"previously",
"learned",
"features.",
"This",
"paper",
"presents",
"Bilevel",
"Continual",
"Learning",
"(BiCL),",
"a",
"general",
"framework",
"for",
"continual",
"learning",
"that",
"fuses",
"bilevel",
"optimization",
"and",
"recent",
"advances",
"in",
"meta-learning",
"for",
"deep",
"neural",
"networks.",
"BiCL",
"is",
"able",
"to",
"train",
"both",
"deep",
"discriminative",
"and",
"generative",
"models",
"under",
"the",
"conservative",
"setting",
"of",
"the",
"online",
"continual",
"learning.",
"Experimental",
"results",
"show",
"that",
"BiCL",
"provides",
"competitive",
"performance",
"in",
"terms",
"of",
"accuracy",
"for",
"the",
"current",
"task",
"while",
"reducing",
"the",
"effect",
"of",
"catastrophic",
"forgetting.",
"This",
"is",
"a",
"concurrent",
"work",
"with",
"[1].",
"We",
"submitted",
"it",
"to",
"AAAI",
"2020",
"and",
"IJCAI",
"2020",
"Now",
"we",
"put",
"it",
"on",
"the",
"arxiv",
"for",
"record.",
"Different",
"from",
"[1],",
"we",
"also",
"consider",
"continual",
"generative",
"model",
"as",
"well.",
"At",
"the",
"same",
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"the",
"authors",
"are",
"aware",
"of",
"a",
"recent",
"proposal",
"on",
"bilevel",
"optimization",
"based",
"coreset",
"construction",
"for",
"continual",
"learning",
"[2].",
"[1]",
"Q.",
"Pham,",
"D.",
"Sahoo,",
"C.",
"Liu,",
"and",
"S.",
"C.",
"Hoi.",
"Bilevel",
"continual",
"learning.",
"arXiv",
"preprint",
"arXiv:2007.15553,",
"2020",
"[2]",
"Z.",
"Borsos,",
"M.",
"Mutny,",
"and",
"A.",
"Krause.",
"Coresets",
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"bilevel",
"optimization",
"for",
"continual",
"learning",
"and",
"streaming.",
"arXiv",
"preprint",
"arXiv:2006.03875,",
"2020"
] |
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[
"Triggered",
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"development,",
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"sources.",
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"fact",
"that",
"publications",
"are",
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"with",
"inaccurate",
"data.",
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"topic",
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"the",
"last",
"5",
"years.",
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"is",
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"data",
"verification",
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"a",
"challenge",
"even",
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"the",
"experts.",
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"paper",
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"a",
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"fact",
"checking",
"system.",
"It",
"can",
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"fact",
"verification",
"problem",
"entirely",
"or",
"at",
"the",
"individual",
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"proposed",
"model",
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"various",
"advanced",
"methods",
"of",
"text",
"data",
"analysis,",
"such",
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"BERT",
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"theoretical",
"and",
"empirical",
"study",
"of",
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"system",
"features",
"is",
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"out.",
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"Challenge",
"test-collections,",
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"datasets."
] |
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[
"Named",
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")",
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"NER",
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"NER",
",",
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"NER",
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"subtasks",
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"representations",
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"datasets,",
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"NER",
"datasets,",
"three",
"nested",
"NER",
"datasets,",
"and",
"three",
"discontinuous",
"NER",
"datasets."
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"have",
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"Wikipedia",
"to",
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"take",
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"model",
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"appropriate",
"answers,",
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"1.1,",
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"BERT",
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"annotated",
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"approaches",
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"also",
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"our",
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] |
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"search",
"method,",
"DifferentiableArchitecture",
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"general,",
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"infinal",
"model",
"error",
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"and",
"5.50%",
"error",
"(5.8+/-0.3)on",
"the",
"recently",
"released",
"CIFAR-10.1",
"test",
"set.",
"To",
"our",
"knowledge,",
"both",
"are",
"stateof",
"the",
"art",
"for",
"models",
"of",
"similar",
"size.",
"This",
"model",
"also",
"generalizescompetitively",
"to",
"ImageNet",
"at",
"25.10%",
"top-1",
"(7.8%",
"top-5)",
"error.",
"We",
"found",
"improvements",
"for",
"existing",
"search",
"spaces",
"but",
"does",
"DARTS",
"generalize",
"tonew",
"domains?",
"We",
"propose",
"Differentiable",
"Hyperparameter",
"Grid",
"Search",
"and",
"theHyperCuboid",
"search",
"space,",
"which",
"are",
"representations",
"designed",
"to",
"leverage",
"DARTS",
"for",
"more",
"general",
"parameter",
"optimization.",
"Here",
"we",
"find",
"that",
"DARTS",
"fails",
"togeneralize",
"when",
"compared",
"against",
"a",
"human's",
"one",
"shot",
"choice",
"of",
"models.",
"We",
"lookback",
"to",
"the",
"DARTS",
"and",
"sharpDARTS",
"search",
"spaces",
"to",
"understand",
"why,",
"and",
"anablation",
"study",
"reveals",
"an",
"unusual",
"generalization",
"gap.",
"We",
"finally",
"propose",
"Max-Wregularization",
"to",
"solve",
"this",
"problem,",
"which",
"proves",
"significantly",
"better",
"thanthe",
"handmade",
"design.",
"Code",
"will",
"be",
"made",
"available."
] |
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[
"This",
"paper",
"describes",
"SENSELEARNER",
"--",
"a",
"minimally",
"supervised",
"word",
"sense",
"disambiguation",
"system",
"that",
"attempts",
"to",
"disambiguate",
"all",
"content",
"words",
"in",
"a",
"text",
"using",
"WordNet",
"senses",
".",
"We",
"evaluate",
"the",
"accuracy",
"of",
"SENSELEARNER",
"on",
"several",
"standard",
"sense-annotated",
"data",
"sets",
",",
"and",
"show",
"that",
"it",
"compares",
"favorably",
"with",
"the",
"best",
"results",
"reported",
"during",
"the",
"recent",
"SENSEVAL",
"evaluations",
"."
] |
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[
"In",
"this",
"paper,",
"in",
"following",
"of",
"the",
"first",
"part",
"(which",
"ADF",
"tests",
"using",
"ACI",
"evaluation)",
"has",
"conducted,",
"Time",
"Series",
"(TS",
"s)",
"are",
"analyzed",
"using",
"decomposition",
"analysis.",
"In",
"fact,",
"TS",
"s",
"are",
"composed",
"of",
"four",
"components",
"including",
"trend",
"(long",
"term",
"behavior",
"or",
"progression",
"of",
"series),",
"cyclic",
"component",
"(non-periodic",
"fluctuation",
"behavior",
"which",
"are",
"usually",
"long",
"term),",
"seasonal",
"component",
"(periodic",
"fluctuations",
"due",
"to",
"seasonal",
"variations",
"like",
"temperature,",
"weather",
"condition",
"and",
"etc.)",
"and",
"error",
"term.",
"For",
"our",
"case",
"of",
"cyber-attack",
"detection,",
"in",
"this",
"paper,",
"two",
"common",
"ways",
"of",
"TS",
"decomposition",
"are",
"investigated.",
"The",
"first",
"method",
"is",
"additive",
"decomposition",
"and",
"the",
"second",
"is",
"multiplicative",
"method",
"to",
"decompose",
"a",
"TS",
"into",
"its",
"components.",
"After",
"decomposition,",
"the",
"error",
"term",
"is",
"tested",
"using",
"Durbin-Watson",
"and",
"Breusch-Godfrey",
"test",
"to",
"see",
"whether",
"the",
"error",
"follows",
"any",
"predictable",
"pattern,",
"it",
"can",
"be",
"concluded",
"that",
"there",
"is",
"a",
"chance",
"of",
"cyber-attack",
"to",
"the",
"system."
] |
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[
"Deep",
"Generative",
"Networks",
"(DGNs)",
"with",
"probabilistic",
"modeling",
"of",
"their",
"outputand",
"latent",
"space",
"are",
"currently",
"trained",
"via",
"Variational",
"Autoencoders(VAE",
"s).In",
"the",
"absence",
"of",
"a",
"known",
"analytical",
"form",
"for",
"the",
"posterior",
"andlikelihood",
"expectation,",
"VAE",
"s",
"resort",
"to",
"approximations,",
"including(Amortized)",
"Variational",
"Inference",
"(AVI)",
"and",
"Monte-Carlosampling.We",
"exploit",
"the",
"Continuous",
"Piecewise",
"Affinepropertyof",
"modern",
"DGNs",
"to",
"derive",
"their",
"posterior",
"and",
"marginaldistributions",
"as",
"well",
"as",
"the",
"latter's",
"first",
"two",
"moments.",
"These",
"findings",
"enable",
"us",
"to",
"derive",
"an",
"analytical",
"Expectation-Maximization",
"(EM)",
"algorithm",
"for",
"gradient-free",
"DGN",
"learning.We",
"demonstrate",
"empirically",
"that",
"EM",
"training",
"of",
"DGNs",
"produces",
"greaterlikelihood",
"than",
"VAE",
"training.Our",
"new",
"framework",
"will",
"guide",
"the",
"design",
"of",
"new",
"VAE",
"AVI",
"that",
"better",
"approximates",
"the",
"TRUE",
"posterior",
"and",
"open",
"new",
"avenues",
"to",
"apply",
"standard",
"statistical",
"tools",
"for",
"model",
"comparison,",
"anomaly",
"detection,",
"and",
"missing",
"data",
"imputation."
] |
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[
"In",
"this",
"work,",
"we",
"examine",
"the",
"ability",
"of",
"NER",
"models",
"to",
"use",
"contextual",
"information",
"when",
"predicting",
"the",
"type",
"of",
"an",
"ambiguous",
"entity.",
"We",
"introduce",
"NRB,",
"a",
"new",
"testbed",
"carefully",
"designed",
"to",
"diagnose",
"Name",
"Regularity",
"Bias",
"of",
"NER",
"models.",
"Our",
"results",
"indicate",
"that",
"all",
"state-of-the-art",
"models",
"we",
"tested",
"show",
"such",
"a",
"bias;",
"BERT",
"fine-tuned",
"models",
"significantly",
"outperforming",
"feature-based",
"(LSTM-CRF)",
"ones",
"on",
"NRB,",
"despite",
"having",
"comparable",
"(sometimes",
"lower)",
"performance",
"on",
"standard",
"benchmarks.",
"To",
"mitigate",
"this",
"bias,",
"we",
"propose",
"a",
"novel",
"model-agnostic",
"training",
"method",
"that",
"adds",
"learnable",
"adversarial",
"noise",
"to",
"some",
"entity",
"mentions,",
"thus",
"enforcing",
"models",
"to",
"focus",
"more",
"strongly",
"on",
"the",
"contextual",
"signal,",
"leading",
"to",
"significant",
"gains",
"on",
"NRB.",
"Combining",
"it",
"with",
"two",
"other",
"training",
"strategies,",
"data",
"augmentation",
"and",
"parameter",
"freezing,",
"leads",
"to",
"further",
"gains."
] |
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[
"Systems",
"exhibiting",
"nonlinear",
"dynamics,",
"including",
"but",
"not",
"limited",
"to",
"chaos,",
"are",
"ubiquitous",
"across",
"Earth",
"Sciences",
"such",
"as",
"Meteorology,",
"Hydrology,",
"Climate",
"and",
"Ecology,",
"as",
"well",
"as",
"Biology",
"such",
"as",
"neural",
"and",
"cardiac",
"processes.",
"However,",
"System",
"Identification",
"remains",
"a",
"challenge.",
"In",
"climate",
"and",
"earth",
"systems",
"models,",
"while",
"governing",
"equations",
"follow",
"from",
"first",
"principles",
"and",
"understanding",
"of",
"key",
"processes",
"has",
"steadily",
"improved,",
"the",
"largest",
"uncertainties",
"are",
"often",
"caused",
"by",
"parameterizations",
"such",
"as",
"cloud",
"physics,",
"which",
"in",
"turn",
"have",
"witnessed",
"limited",
"improvements",
"over",
"the",
"last",
"several",
"decades.",
"Climate",
"scientists",
"have",
"pointed",
"to",
"Machine",
"Learning",
"enhanced",
"parameter",
"estimation",
"as",
"a",
"possible",
"solution,",
"with",
"proof-of-concept",
"methodological",
"adaptations",
"being",
"examined",
"on",
"idealized",
"systems.",
"While",
"climate",
"science",
"has",
"been",
"highlighted",
"as",
"a",
"Big\tO\nData",
"challenge",
"owing",
"to",
"the",
"volume",
"and",
"complexity",
"of",
"archived",
"model-simulations",
"and",
"observations",
"from",
"remote",
"and",
"in-situ",
"sensors,",
"the",
"parameter",
"estimation",
"process",
"is",
"often",
"relatively",
"a",
"small\tO\ndata",
"problem.",
"A",
"crucial",
"question",
"for",
"data",
"scientists",
"in",
"this",
"context",
"is",
"the",
"relevance",
"of",
"state-of-the-art",
"data-driven",
"approaches",
"including",
"those",
"based",
"on",
"deep",
"neural",
"networks",
"or",
"kernel-based",
"processes.",
"Here",
"we",
"consider",
"a",
"chaotic",
"system",
"-",
"two-level",
"Lorenz-96",
"-",
"used",
"as",
"a",
"benchmark",
"model",
"in",
"the",
"climate",
"science",
"literature,",
"adopt",
"a",
"methodology",
"based",
"on",
"Gaussian",
"Processes",
"for",
"parameter",
"estimation",
"and",
"compare",
"the",
"gains",
"in",
"predictive",
"understanding",
"with",
"a",
"suite",
"of",
"Deep",
"Learning",
"and",
"strawman",
"Linear",
"Regression",
"methods.",
"Our",
"results",
"show",
"that",
"adaptations",
"of",
"kernel-based",
"Gaussian",
"Processes",
"can",
"outperform",
"other",
"approaches",
"under",
"small",
"data",
"constraints",
"along",
"with",
"uncertainty",
"quantification;",
"and",
"needs",
"to",
"be",
"considered",
"as",
"a",
"viable",
"approach",
"in",
"climate",
"science",
"and",
"earth",
"system",
"modeling."
] |
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[
"In",
"this",
"paper,",
"we",
"propose",
"a",
"simple",
"and",
"general",
"framework",
"for",
"training",
"verytiny",
"CNNs",
"for",
"object",
"detection.",
"Due",
"to",
"limited",
"representation",
"ability,",
"it",
"ischallenging",
"to",
"train",
"very",
"tiny",
"networks",
"for",
"complicated",
"tasks",
"like",
"detection.To",
"the",
"best",
"of",
"our",
"knowledge,",
"our",
"method,",
"called",
"Quantization",
"Mimic,",
"is",
"thefirst",
"one",
"focusing",
"on",
"very",
"tiny",
"networks.",
"We",
"utilize",
"two",
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"of",
"accelerationmethods:",
"mimic",
"and",
"quantization.",
"Mimic",
"improves",
"the",
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"studentnetwork",
"by",
"transfering",
"knowledge",
"from",
"a",
"teacher",
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"Quantization",
"convertsa",
"full-precision",
"network",
"to",
"a",
"quantized",
"one",
"without",
"large",
"degradation",
"ofperformance.",
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"the",
"teacher",
"network",
"is",
"quantized,",
"the",
"search",
"scope",
"of",
"thestudent",
"network",
"will",
"be",
"smaller.",
"Using",
"this",
"feature",
"of",
"the",
"quantization,",
"wepropose",
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"Mimic.",
"It",
"first",
"quantizes",
"the",
"large",
"network,",
"then",
"mimic",
"aquantized",
"small",
"network.",
"The",
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"operation",
"can",
"help",
"student",
"network",
"tobetter",
"match",
"the",
"feature",
"maps",
"from",
"teacher",
"network.",
"To",
"evaluate",
"our",
"approach,we",
"carry",
"out",
"experiments",
"on",
"various",
"popular",
"CNNs",
"including",
"VGG",
"and",
"Resnet,",
"aswell",
"as",
"different",
"detection",
"frameworks",
"including",
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"R-CNN",
"and",
"R-FCN.Experiments",
"on",
"Pascal",
"VOC",
"and",
"WIDER",
"FACE",
"verify",
"that",
"our",
"Quantization",
"Mimicalgorithm",
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"be",
"applied",
"on",
"various",
"settings",
"and",
"outperforms",
"state-of-the-artmodel",
"acceleration",
"methods",
"given",
"limited",
"computing",
"resouces."
] |
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[
"We",
"propose",
"a",
"scheme",
"for",
"defending",
"against",
"adversarial",
"attacks",
"by",
"suppressing",
"the",
"largest",
"eigenvalue",
"of",
"the",
"Fisher",
"information",
"matrix",
"(FIM).",
"Our",
"starting",
"point",
"is",
"one",
"explanation",
"on",
"the",
"rationale",
"of",
"adversarial",
"examples.",
"Based",
"on",
"the",
"idea",
"of",
"the",
"difference",
"between",
"a",
"benign",
"sample",
"and",
"its",
"adversarial",
"example",
"is",
"measured",
"by",
"the",
"Euclidean",
"norm,",
"while",
"the",
"difference",
"between",
"their",
"classification",
"probability",
"densities",
"at",
"the",
"last",
"(softmax)",
"layer",
"of",
"the",
"network",
"could",
"be",
"measured",
"by",
"the",
"Kullback-Leibler",
"(KL)",
"divergence,",
"the",
"explanation",
"shows",
"that",
"the",
"output",
"difference",
"is",
"a",
"quadratic",
"form",
"of",
"the",
"input",
"difference.",
"If",
"the",
"eigenvalue",
"of",
"this",
"quadratic",
"form",
"(a.k.a.",
"FIM)",
"is",
"large,",
"the",
"output",
"difference",
"becomes",
"large",
"even",
"when",
"the",
"input",
"difference",
"is",
"small,",
"which",
"explains",
"the",
"adversarial",
"phenomenon.",
"This",
"makes",
"the",
"adversarial",
"defense",
"possible",
"by",
"controlling",
"the",
"eigenvalues",
"of",
"the",
"FIM.",
"Our",
"solution",
"is",
"adding",
"one",
"term",
"representing",
"the",
"trace",
"of",
"the",
"FIM",
"to",
"the",
"loss",
"function",
"of",
"the",
"original",
"network,",
"as",
"the",
"largest",
"eigenvalue",
"is",
"bounded",
"by",
"the",
"trace.",
"Our",
"defensive",
"scheme",
"is",
"verified",
"by",
"experiments",
"using",
"a",
"variety",
"of",
"common",
"attacking",
"methods",
"on",
"typical",
"deep",
"neural",
"networks,",
"e.g.",
"LeNet,",
"VGG",
"and",
"ResNet,",
"with",
"datasets",
"MNIST,",
"CIFAR-10,",
"and",
"German",
"Traffic",
"Sign",
"Recognition",
"Benchmark",
"(GTSRB).",
"Our",
"new",
"network,",
"after",
"adopting",
"the",
"novel",
"loss",
"function",
"and",
"retraining,",
"has",
"an",
"effective",
"and",
"robust",
"defensive",
"capability,",
"as",
"it",
"decreases",
"the",
"fooling",
"ratio",
"of",
"the",
"generated",
"adversarial",
"examples,",
"and",
"remains",
"the",
"classification",
"accuracy",
"of",
"the",
"original",
"network."
] |
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[
"Task-agnostic",
"pre-training",
"followed",
"by",
"task-specific",
"fine-tuning",
"is",
"a",
"default",
"approach",
"to",
"train",
"NLU",
"models.",
"Such",
"models",
"need",
"to",
"be",
"deployed",
"on",
"devices",
"across",
"the",
"cloud",
"and",
"the",
"edge",
"with",
"varying",
"resource",
"and",
"accuracy",
"constraints.",
"For",
"a",
"given",
"task,",
"repeating",
"pre-training",
"and",
"fine-tuning",
"across",
"tens",
"of",
"devices",
"is",
"prohibitively",
"expensive.",
"We",
"propose",
"SuperShaper,",
"a",
"task",
"agnostic",
"pre-training",
"approach",
"which",
"simultaneously",
"pre-trains",
"a",
"large",
"number",
"of",
"Transformer",
"models",
"by",
"varying",
"shapes,",
"i.e.,",
"by",
"varying",
"the",
"hidden",
"dimensions",
"across",
"layers.",
"This",
"is",
"enabled",
"by",
"a",
"backbone",
"network",
"with",
"linear",
"bottleneck",
"matrices",
"around",
"each",
"Transformer",
"layer",
"which",
"are",
"sliced",
"to",
"generate",
"differently",
"shaped",
"sub-networks.",
"In",
"spite",
"of",
"its",
"simple",
"design",
"space",
"and",
"efficient",
"implementation,",
"SuperShaper",
"discovers",
"networks",
"that",
"effectively",
"trade-off",
"accuracy",
"and",
"model",
"size:",
"Discovered",
"networks",
"are",
"more",
"accurate",
"than",
"a",
"range",
"of",
"hand-crafted",
"and",
"automatically",
"searched",
"networks",
"on",
"GLUE",
"benchmarks.",
"Further,",
"we",
"find",
"two",
"critical",
"advantages",
"of",
"shape",
"as",
"a",
"design",
"variable",
"for",
"Neural",
"Architecture",
"Search",
"(NAS):",
"(a)",
"heuristics",
"of",
"good",
"shapes",
"can",
"be",
"derived",
"and",
"networks",
"found",
"with",
"these",
"heuristics",
"match",
"and",
"even",
"improve",
"on",
"carefully",
"searched",
"networks",
"across",
"a",
"range",
"of",
"parameter",
"counts,",
"and",
"(b)",
"the",
"latency",
"of",
"networks",
"across",
"multiple",
"CPUs",
"and",
"GPUs",
"are",
"insensitive",
"to",
"the",
"shape",
"and",
"thus",
"enable",
"device-agnostic",
"search.",
"In",
"summary,",
"SuperShaper",
"radically",
"simplifies",
"NAS",
"for",
"language",
"models",
"and",
"discovers",
"networks",
"that",
"generalize",
"across",
"tasks,",
"parameter",
"constraints,",
"and",
"devices."
] |
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"Designing",
"an",
"effective",
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"plays",
"an",
"important",
"role",
"in",
"visual",
"analysis.",
"Most",
"existing",
"loss",
"function",
"designs",
"rely",
"on",
"hand-crafted",
"heuristics",
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"require",
"domain",
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"explore",
"the",
"large",
"design",
"space,",
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"and",
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"this",
"paper,",
"we",
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"for",
"Loss",
"Function",
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"leverages",
"REINFORCE",
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"search",
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"functions",
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"training",
"process.",
"The",
"key",
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"work",
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"the",
"design",
"of",
"search",
"space",
"which",
"can",
"guarantee",
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"tasks",
"by",
"including",
"a",
"bunch",
"of",
"existing",
"prevailing",
"loss",
"functions",
"in",
"a",
"unified",
"formulation.",
"We",
"also",
"propose",
"an",
"efficient",
"optimization",
"framework",
"which",
"can",
"dynamically",
"optimize",
"the",
"parameters",
"of",
"loss",
"function's",
"distribution",
"during",
"training.",
"Extensive",
"experimental",
"results",
"on",
"four",
"benchmark",
"datasets",
"show",
"that,",
"without",
"any",
"tricks,",
"our",
"method",
"outperforms",
"existing",
"hand-crafted",
"loss",
"functions",
"in",
"various",
"computer",
"vision",
"tasks."
] |
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"Underwater",
"image",
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"has",
"attracted",
"much",
"attention",
"due",
"to",
"the",
"rise",
"of",
"marine",
"resource",
"development",
"in",
"recent",
"years.",
"Benefit",
"from",
"the",
"powerful",
"representation",
"capabilities",
"of",
"Convolution",
"Neural",
"Networks(CNNs),",
"multiple",
"underwater",
"image",
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"algorithms",
"based",
"on",
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"have",
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"proposed",
"in",
"the",
"last",
"few",
"years.",
"However,",
"almost",
"all",
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"these",
"algorithms",
"employ",
"RGB",
"color",
"space",
"setting,",
"which",
"is",
"insensitive",
"to",
"image",
"properties",
"such",
"as",
"luminance",
"and",
"saturation.",
"To",
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"transformations",
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"methods",
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"and",
"global-level",
"selections,",
"to",
"pick",
"suitable",
"samples",
"for",
"distillation.",
"We",
"evaluate",
"our",
"approaches",
"on",
"two",
"large-scale",
"machine",
"translation",
"tasks,",
"WMT'14",
"English->German",
"and",
"WMT'19",
"Chinese->English.",
"Experimental",
"results",
"show",
"that",
"our",
"approaches",
"yield",
"up",
"to",
"1.28",
"and",
"0.89",
"BLEU",
"points",
"improvements",
"over",
"the",
"Transformer",
"baseline,",
"respectively."
] |
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[
"Intent",
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"systems",
"in",
"the",
"real",
"world",
"are",
"exposed",
"to",
"complexities",
"of",
"imbalanced",
"datasets",
"containing",
"varying",
"perception",
"of",
"intent,",
"unintended",
"correlations",
"and",
"domain-specific",
"aberrations.",
"To",
"facilitate",
"benchmarking",
"which",
"can",
"reflect",
"near",
"real-world",
"scenarios,",
"we",
"introduce",
"3",
"new",
"datasets",
"created",
"from",
"live",
"chatbots",
"in",
"diverse",
"domains.",
"Unlike",
"most",
"existing",
"datasets",
"that",
"are",
"crowdsourced,",
"our",
"datasets",
"contain",
"real",
"user",
"queries",
"received",
"by",
"the",
"chatbots",
"and",
"facilitates",
"penalising",
"unwanted",
"correlations",
"grasped",
"during",
"the",
"training",
"process.",
"We",
"evaluate",
"4",
"NLU",
"platforms",
"and",
"a",
"BERT",
"based",
"classifier",
"and",
"find",
"that",
"performance",
"saturates",
"at",
"inadequate",
"levels",
"on",
"test",
"sets",
"because",
"all",
"systems",
"latch",
"on",
"to",
"unintended",
"patterns",
"in",
"training",
"data."
] |
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[
"We",
"investigate",
"the",
"impact",
"of",
"aggressive",
"low-precision",
"representations",
"of",
"weights",
"and",
"activations",
"in",
"two",
"families",
"of",
"large",
"LSTM",
"#NAME?",
"architectures",
"for",
"Automatic",
"Speech",
"Recognition",
"(ASR):",
"hybrid",
"Deep",
"Bidirectional",
"LSTM",
"-",
"Hidden",
"Markov",
"Models",
"(DBLSTM",
"-HMMs)",
"and",
"Recurrent",
"Neural",
"Network",
"-",
"Transducers",
"(RNN-Ts).",
"Using",
"a",
"4-bit",
"integer",
"representation,",
"a",
"na\\\"ive",
"quantization",
"approach",
"applied",
"to",
"the",
"LSTM",
"portion",
"of",
"these",
"models",
"results",
"in",
"significant",
"Word",
"Error",
"Rate",
"(WER)",
"degradation.",
"On",
"the",
"other",
"hand,",
"we",
"show",
"that",
"minimal",
"accuracy",
"loss",
"is",
"achievable",
"with",
"an",
"appropriate",
"choice",
"of",
"quantizers",
"and",
"initializations.",
"In",
"particular,",
"we",
"customize",
"quantization",
"schemes",
"depending",
"on",
"the",
"local",
"properties",
"of",
"the",
"network,",
"improving",
"recognition",
"performance",
"while",
"limiting",
"computational",
"time.",
"We",
"demonstrate",
"our",
"solution",
"on",
"the",
"Switchboard",
"(SWB)",
"and",
"CallHome",
"(CH)",
"test",
"sets",
"of",
"the",
"NIST",
"Hub5-2000",
"evaluation.",
"DBLSTM",
"#NAME?",
"trained",
"with",
"300",
"or",
"2000",
"hours",
"of",
"SWB",
"data",
"achieves",
"$<$0.5%",
"and",
"$<$1%",
"average",
"WER",
"degradation,",
"respectively.",
"On",
"the",
"more",
"challenging",
"RNN-T",
"models,",
"our",
"quantization",
"strategy",
"limits",
"degradation",
"in",
"4-bit",
"inference",
"to",
"1.3%."
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[
"Conventional",
"approaches",
"to",
"Sketch-Based",
"Image",
"Retrieval",
"(SBIR)",
"assume",
"that",
"the",
"data",
"of",
"all",
"the",
"classes",
"are",
"available",
"during",
"training.",
"The",
"assumption",
"may",
"not",
"always",
"be",
"practical",
"since",
"the",
"data",
"of",
"a",
"few",
"classes",
"may",
"be",
"unavailable,",
"or",
"the",
"classes",
"may",
"not",
"appear",
"at",
"the",
"time",
"of",
"training.",
"Zero-Shot",
"Sketch-Based",
"Image",
"Retrieval",
"(ZS-SBIR)",
"relaxes",
"this",
"constraint",
"and",
"allows",
"the",
"algorithm",
"to",
"handle",
"previously",
"unseen",
"classes",
"during",
"the",
"test.",
"This",
"paper",
"proposes",
"a",
"generative",
"approach",
"based",
"on",
"the",
"Stacked",
"Adversarial",
"Network",
"(SAN)",
"and",
"the",
"advantage",
"of",
"Siamese",
"Network",
"(SN)",
"for",
"ZS-SBIR.",
"While",
"SAN",
"generates",
"a",
"high-quality",
"sample,",
"SN",
"learns",
"a",
"better",
"distance",
"metric",
"compared",
"to",
"that",
"of",
"the",
"nearest",
"neighbor",
"search.",
"The",
"capability",
"of",
"the",
"generative",
"model",
"to",
"synthesize",
"image",
"features",
"based",
"on",
"the",
"sketch",
"reduces",
"the",
"SBIR",
"problem",
"to",
"that",
"of",
"an",
"image-to-image",
"retrieval",
"problem.",
"We",
"evaluate",
"the",
"efficacy",
"of",
"our",
"proposed",
"approach",
"on",
"TU-Berlin,",
"and",
"Sketchy",
"database",
"in",
"both",
"standard",
"ZSL",
"and",
"generalized",
"ZSL",
"setting.",
"The",
"proposed",
"method",
"yields",
"a",
"significant",
"improvement",
"in",
"standard",
"ZSL",
"as",
"well",
"as",
"in",
"a",
"more",
"challenging",
"generalized",
"ZSL",
"setting",
"(GZSL)",
"for",
"SBIR."
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[
"Presence",
"of",
"noise",
"in",
"the",
"labels",
"of",
"large",
"scale",
"facial",
"expression",
"datasets",
"has",
"been",
"a",
"key",
"challenge",
"towards",
"Facial",
"Expression",
"Recognition",
"(FER)",
"in",
"the",
"wild.",
"During",
"early",
"learning",
"stage,",
"deep",
"networks",
"fit",
"on",
"clean",
"data.",
"Then,",
"eventually,",
"they",
"start",
"overfitting",
"on",
"noisy",
"labels",
"due",
"to",
"their",
"memorization",
"ability,",
"which",
"limits",
"FER",
"performance.",
"This",
"work",
"proposes",
"an",
"effective",
"training",
"strategy",
"in",
"the",
"presence",
"of",
"noisy",
"labels,",
"called",
"as",
"Consensual",
"Collaborative",
"Training",
"(CCT",
")",
"framework.",
"CCT",
"co-trains",
"three",
"networks",
"jointly",
"using",
"a",
"convex",
"combination",
"of",
"supervision",
"loss",
"and",
"consistency",
"loss,",
"without",
"making",
"any",
"assumption",
"about",
"the",
"noise",
"distribution.",
"A",
"dynamic",
"transition",
"mechanism",
"is",
"used",
"to",
"move",
"from",
"supervision",
"loss",
"in",
"early",
"learning",
"to",
"consistency",
"loss",
"for",
"consensus",
"of",
"predictions",
"among",
"networks",
"in",
"the",
"later",
"stage.",
"Inference",
"is",
"done",
"using",
"a",
"single",
"network",
"based",
"on",
"a",
"simple",
"knowledge",
"distillation",
"scheme.",
"Effectiveness",
"of",
"the",
"proposed",
"framework",
"is",
"demonstrated",
"on",
"synthetic",
"as",
"well",
"as",
"real",
"noisy",
"FER",
"datasets.",
"In",
"addition,",
"a",
"large",
"test",
"subset",
"of",
"around",
"5K",
"images",
"is",
"annotated",
"from",
"the",
"FEC",
"dataset",
"using",
"crowd",
"wisdom",
"of",
"16",
"different",
"annotators",
"and",
"reliable",
"labels",
"are",
"inferred.",
"CCT",
"is",
"also",
"validated",
"on",
"it.",
"State-of-the-art",
"performance",
"is",
"reported",
"on",
"the",
"benchmark",
"FER",
"datasets",
"RAFDB",
"-90.84%",
"FERPlus",
"-89.99%",
"and",
"AffectNet",
"(66%).",
"Our",
"codes",
"are",
"available",
"at",
"https://github.com/1980x/CCT",
"."
] |
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[
"The",
"impressive",
"capabilities",
"of",
"recent",
"generative",
"models",
"to",
"create",
"texts",
"that",
"are",
"challenging",
"to",
"distinguish",
"from",
"the",
"human-written",
"ones",
"can",
"be",
"misused",
"for",
"generating",
"fake",
"news,",
"product",
"reviews,",
"and",
"even",
"abusive",
"content.",
"Despite",
"the",
"prominent",
"performance",
"of",
"existing",
"methods",
"for",
"artificial",
"text",
"detection,",
"they",
"still",
"lack",
"interpretability",
"and",
"robustness",
"towards",
"unseen",
"models.",
"To",
"this",
"end,",
"we",
"propose",
"three",
"novel",
"types",
"of",
"interpretable",
"topological",
"features",
"for",
"this",
"task",
"based",
"on",
"Topological",
"Data",
"Analysis",
"(TDA)",
"which",
"is",
"currently",
"understudied",
"in",
"the",
"field",
"of",
"NLP.",
"We",
"empirically",
"show",
"that",
"the",
"features",
"derived",
"from",
"the",
"BERT",
"model",
"outperform",
"count-",
"and",
"neural-based",
"baselines",
"up",
"to",
"10\\%",
"on",
"three",
"common",
"datasets,",
"and",
"tend",
"to",
"be",
"the",
"most",
"robust",
"towards",
"unseen",
"GPT-style",
"generation",
"models",
"as",
"opposed",
"to",
"existing",
"methods.",
"The",
"probing",
"analysis",
"of",
"the",
"features",
"reveals",
"their",
"sensitivity",
"to",
"the",
"surface",
"and",
"syntactic",
"properties.",
"The",
"results",
"demonstrate",
"that",
"TDA",
"is",
"a",
"promising",
"line",
"with",
"respect",
"to",
"NLP",
"tasks,",
"specifically",
"the",
"ones",
"that",
"incorporate",
"surface",
"and",
"structural",
"information."
] |
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"challenging",
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"vision,",
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"address",
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"mask",
"prediction",
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"to",
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"two-stage",
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"detector",
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"Proposal",
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"producing",
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"results,",
"the",
"efficiency",
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"these",
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"approaches",
"is",
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"from",
"satisfactory,",
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"practice.",
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"this",
"paper,",
"we",
"propose",
"a",
"one-stage",
"framework,",
"SPRNet,",
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"efficient",
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"segmentation",
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"introducing",
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"one-stage",
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"pixel",
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"map",
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"same",
"ResNet-50",
"backbone,",
"SPRNet",
"achieves",
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"mask",
"AP",
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"speed,",
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"at",
"every",
"scale",
"comparing",
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"Research",
"Council",
"Canada",
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"baseline",
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"n-grams",
"and",
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"were",
"trained,",
"and",
"analyze",
"the",
"impact",
"of",
"some",
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"and",
"model",
"estimation",
"decisions.",
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"deep",
"neural",
"network",
"achieved",
"77{\\%}",
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"on",
"the",
"test",
"data,",
"which",
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"establishing",
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"for",
"cuneiform",
"language",
"identification."
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"order",
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",",
"we",
"show",
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"compared",
"to",
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"."
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"users.",
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"and",
"more",
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"the",
"sentimental",
"tendency",
"of",
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"have",
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"based",
"on",
"the",
"sentiment",
"classification",
"of",
"explicit",
"texts.",
"However,",
"research",
"on",
"the",
"implicit",
"sentiment",
"of",
"users",
"is",
"still",
"in",
"its",
"infancy.",
"Aiming",
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"sentiment",
"classification,",
"a",
"research",
"on",
"implicit",
"sentiment",
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"model",
"based",
"on",
"deep",
"neural",
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"carried",
"out.",
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"based",
"on",
"DNN,",
"LSTM",
",",
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"and",
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"implicit",
"sentiment",
"text.",
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"on",
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"Bi-LSTM",
"model,",
"the",
"classification",
"model",
"of",
"word-level",
"attention",
"mechanism",
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"experimental",
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"on",
"the",
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"show",
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"the",
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"LSTM",
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"classification",
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"model",
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"effect,",
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"Recent",
"developments",
"in",
"Named",
"Entity",
"Recognition",
"(NER)",
"have",
"resulted",
"in",
"better",
"and",
"better",
"models.",
"However,",
"is",
"there",
"a",
"glass",
"ceiling?",
"Do",
"we",
"know",
"which",
"types",
"of",
"errors",
"are",
"still",
"hard",
"or",
"even",
"impossible",
"to",
"correct?",
"In",
"this",
"paper,",
"we",
"present",
"a",
"detailed",
"analysis",
"of",
"the",
"types",
"of",
"errors",
"in",
"state-of-the-art",
"machine",
"learning",
"(ML)",
"methods.",
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"and",
"strong",
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"of",
"the",
"Stanford,",
"CMU,",
"FLAIR,",
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"and",
"BERT",
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"as",
"well",
"as",
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"shared",
"limitations.",
"We",
"also",
"introduce",
"new",
"techniques",
"for",
"improving",
"annotation,",
"for",
"training",
"processes",
"and",
"for",
"checking",
"a",
"model's",
"quality",
"and",
"stability.",
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"results",
"are",
"based",
"on",
"the",
"CoNLL",
"2003",
"data",
"set",
"for",
"the",
"English",
"language.",
"A",
"new",
"enriched",
"semantic",
"annotation",
"of",
"errors",
"for",
"this",
"data",
"set",
"and",
"new",
"diagnostic",
"data",
"sets",
"are",
"attached",
"in",
"the",
"supplementary",
"materials."
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"A",
"field",
"that",
"has",
"directly",
"benefited",
"from",
"the",
"recent",
"advances",
"in",
"deep",
"learningis",
"Automatic",
"Speech",
"Recognition",
"(ASR).",
"Despite",
"the",
"great",
"achievements",
"of",
"thepast",
"decades,",
"however,",
"a",
"natural",
"and",
"robust",
"human-machine",
"speech",
"interactionstill",
"appears",
"to",
"be",
"out",
"of",
"reach,",
"especially",
"in",
"challenging",
"environmentscharacterized",
"by",
"significant",
"noise",
"and",
"reverberation.",
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"improve",
"robustness,modern",
"speech",
"recognizers",
"often",
"employ",
"acoustic",
"models",
"based",
"on",
"RecurrentNeural",
"Networks",
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"that",
"are",
"naturally",
"able",
"to",
"exploit",
"large",
"time",
"contextsand",
"long-term",
"speech",
"modulations.",
"It",
"is",
"thus",
"of",
"great",
"interest",
"to",
"continue",
"thestudy",
"of",
"proper",
"techniques",
"for",
"improving",
"the",
"effectiveness",
"of",
"RNNs",
"inprocessing",
"speech",
"signals.",
"In",
"this",
"paper,",
"we",
"revise",
"one",
"of",
"the",
"most",
"popular",
"RNN",
"models,",
"namely",
"GatedRecurrent",
"Units",
"(GRU",
"s),",
"and",
"propose",
"a",
"simplified",
"architecture",
"that",
"turned",
"outto",
"be",
"very",
"effective",
"for",
"ASR.",
"The",
"contribution",
"of",
"this",
"work",
"is",
"two-fold:",
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"analyze",
"the",
"role",
"played",
"by",
"the",
"reset",
"gate,",
"showing",
"that",
"a",
"significantredundancy",
"with",
"the",
"update",
"gate",
"occurs.",
"As",
"a",
"result,",
"we",
"propose",
"to",
"remove",
"theformer",
"from",
"the",
"GRU",
"design,",
"leading",
"to",
"a",
"more",
"efficient",
"and",
"compact",
"single-gatemodel.",
"Second,",
"we",
"propose",
"to",
"replace",
"hyperbolic",
"tangent",
"with",
"ReLU",
"activations.This",
"variation",
"couples",
"well",
"with",
"batch",
"normalization",
"and",
"could",
"help",
"the",
"modellearn",
"long-term",
"dependencies",
"without",
"numerical",
"issues.",
"Results",
"show",
"that",
"the",
"proposed",
"architecture,",
"called",
"Light",
"GRU",
"(Li-GRU",
"),",
"notonly",
"reduces",
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"training",
"time",
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"more",
"than",
"30%",
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"a",
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"GRU",
",but",
"also",
"consistently",
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"the",
"recognition",
"accuracy",
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"different",
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"features,",
"noisy",
"conditions,",
"as",
"well",
"as",
"across",
"different",
"ASR",
"paradigms,ranging",
"from",
"standard",
"DNN-HMM",
"speech",
"recognizers",
"to",
"end-to-end",
"CTC",
"models."
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[
"In",
"this",
"work",
"we",
"address",
"the",
"problem",
"of",
"comparing",
"time",
"series",
"while",
"taking",
"into",
"account",
"both",
"feature",
"space",
"transformation",
"and",
"temporal",
"variability.",
"The",
"proposed",
"framework",
"combines",
"a",
"latent",
"global",
"transformation",
"of",
"the",
"feature",
"space",
"with",
"the",
"widely",
"used",
"Dynamic",
"Time",
"Warping",
"(DTW",
").",
"The",
"latent",
"global",
"transformation",
"captures",
"the",
"feature",
"invariance",
"while",
"the",
"DTW",
"(or",
"its",
"smooth",
"counterpart",
"soft-DTW",
")",
"deals",
"with",
"the",
"temporal",
"shifts.",
"We",
"cast",
"the",
"problem",
"as",
"a",
"joint",
"optimization",
"over",
"the",
"global",
"transformation",
"and",
"the",
"temporal",
"alignments.",
"The",
"versatility",
"of",
"our",
"framework",
"allows",
"for",
"several",
"variants",
"depending",
"on",
"the",
"invariance",
"class",
"at",
"stake.",
"Among",
"our",
"contributions",
"we",
"define",
"a",
"differentiable",
"loss",
"for",
"time",
"series",
"and",
"present",
"two",
"algorithms",
"for",
"the",
"computation",
"of",
"time",
"series",
"barycenters",
"under",
"our",
"new",
"geometry.",
"We",
"illustrate",
"the",
"interest",
"of",
"our",
"approach",
"on",
"both",
"simulated",
"and",
"real",
"world",
"data."
] |
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[
"Neural",
"Architecture",
"Search",
"(NAS),",
"together",
"with",
"model",
"scaling,",
"has",
"shown",
"remarkable",
"progress",
"in",
"designing",
"high",
"accuracy",
"and",
"fast",
"convolutional",
"architecture",
"families.",
"However,",
"as",
"neither",
"NAS",
"nor",
"model",
"scaling",
"considers",
"sufficient",
"hardware",
"architecture",
"details,",
"they",
"do",
"not",
"take",
"full",
"advantage",
"of",
"the",
"emerging",
"datacenter",
"(DC)",
"accelerators.",
"In",
"this",
"paper,",
"we",
"search",
"for",
"fast",
"and",
"accurate",
"CNN",
"model",
"families",
"for",
"efficient",
"inference",
"on",
"DC",
"accelerators.",
"We",
"first",
"analyze",
"DC",
"accelerators",
"and",
"find",
"that",
"existing",
"CNNs",
"suffer",
"from",
"insufficient",
"operational",
"intensity,",
"parallelism,",
"and",
"execution",
"efficiency.",
"These",
"insights",
"let",
"us",
"create",
"a",
"DC-accelerator-optimized",
"search",
"space,",
"with",
"space-to-depth,",
"space-to-batch,",
"hybrid",
"fused",
"convolution",
"structures",
"with",
"vanilla",
"and",
"depthwise",
"convolutions,",
"and",
"block-wise",
"activation",
"functions.",
"On",
"top",
"of",
"our",
"DC",
"accelerator",
"optimized",
"neural",
"architecture",
"search",
"space,",
"we",
"further",
"propose",
"a",
"latency-aware",
"compound",
"scaling",
"(LACS),",
"the",
"first",
"multi-objective",
"compound",
"scaling",
"method",
"optimizing",
"both",
"accuracy",
"and",
"latency.",
"Our",
"LACS",
"discovers",
"that",
"network",
"depth",
"should",
"grow",
"much",
"faster",
"than",
"image",
"size",
"and",
"network",
"width,",
"which",
"is",
"quite",
"different",
"from",
"previous",
"compound",
"scaling",
"results.",
"With",
"the",
"new",
"search",
"space",
"and",
"LACS,",
"our",
"search",
"and",
"scaling",
"on",
"datacenter",
"accelerators",
"results",
"in",
"a",
"new",
"model",
"series",
"named",
"EfficientNet",
"#NAME?",
"EfficientNet",
"#NAME?",
"is",
"up",
"to",
"more",
"than",
"2X",
"faster",
"than",
"EfficientNet",
"(a",
"model",
"series",
"with",
"state-of-the-art",
"trade-off",
"on",
"FLOPs",
"and",
"accuracy)",
"on",
"TPUv3",
"and",
"GPUv100,",
"with",
"comparable",
"accuracy.",
"EfficientNet",
"#NAME?",
"is",
"also",
"up",
"to",
"7X",
"faster",
"than",
"recent",
"RegNet",
"and",
"ResNeSt",
"on",
"TPUv3",
"and",
"GPUv100."
] |
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[
"Building",
"energy",
"performance",
"is",
"one",
"of",
"the",
"key",
"features",
"in",
"performance-based",
"building",
"design",
"decision",
"making.",
"Building",
"envelope",
"materials",
"can",
"play",
"a",
"key",
"role",
"in",
"improving",
"building",
"energy",
"performance.",
"The",
"thermal",
"properties",
"of",
"building",
"materials",
"determine",
"the",
"level",
"of",
"heat",
"transfer",
"through",
"building",
"envelope,",
"thus",
"the",
"annual",
"thermal",
"energy",
"performance",
"of",
"the",
"building.",
"This",
"research",
"applies",
"the",
"Linear",
"Discriminant",
"Analysis",
"(LDA",
")",
"method",
"to",
"study",
"the",
"effects",
"of",
"materials'",
"thermal",
"properties",
"on",
"building",
"thermal",
"loads.",
"Two",
"approaches",
"are",
"adopted",
"for",
"feature",
"selection",
"including",
"the",
"Principal",
"Component",
"Analysis",
"(PCA",
")",
"and",
"the",
"Exhaustive",
"Feature",
"Selection",
"(EFS).",
"A",
"hypothetical",
"design",
"scenario",
"is",
"developed",
"with",
"six",
"material",
"alternatives",
"for",
"an",
"office",
"building",
"in",
"Los",
"Angeles,",
"California.",
"The",
"best",
"design",
"alternative",
"is",
"selected",
"based",
"on",
"the",
"LDA",
"results",
"and",
"the",
"key",
"input",
"parameters",
"are",
"determined",
"based",
"on",
"the",
"PCA",
"and",
"EFS",
"methods.",
"The",
"PCA",
"results",
"confirm",
"that",
"among",
"all",
"thermal",
"properties",
"of",
"the",
"materials,",
"the",
"four",
"parameters",
"including",
"thermal",
"conductivity,",
"density,",
"specific",
"heat",
"capacity,",
"and",
"thickness",
"are",
"the",
"most",
"critical",
"features,",
"in",
"terms",
"of",
"building",
"thermal",
"behavior",
"and",
"thermal",
"energy",
"consumption.",
"This",
"result",
"matches",
"quite",
"well",
"with",
"the",
"assumptions",
"of",
"most",
"of",
"the",
"building",
"energy",
"simulation",
"tools."
] |
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[
"Generative",
"Adversarial",
"Imitation",
"Learning",
"suffers",
"from",
"the",
"fundamental",
"problem",
"of",
"reward",
"bias",
"stemming",
"from",
"the",
"choice",
"of",
"reward",
"functions",
"used",
"in",
"the",
"algorithm.",
"Different",
"types",
"of",
"biases",
"also",
"affect",
"different",
"types",
"of",
"environments",
"-",
"which",
"are",
"broadly",
"divided",
"into",
"survival",
"and",
"task-based",
"environments.",
"We",
"provide",
"a",
"theoretical",
"sketch",
"of",
"why",
"existing",
"reward",
"functions",
"would",
"fail",
"in",
"imitation",
"learning",
"scenarios",
"in",
"task",
"based",
"environments",
"with",
"multiple",
"terminal",
"states.",
"We",
"also",
"propose",
"a",
"new",
"reward",
"function",
"for",
"GAIL",
"which",
"outperforms",
"existing",
"GAIL",
"methods",
"on",
"task",
"based",
"environments",
"with",
"single",
"and",
"multiple",
"terminal",
"states",
"and",
"effectively",
"overcomes",
"both",
"survival",
"and",
"termination",
"bias."
] |
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[
"Recent",
"advancements",
"in",
"attention",
"mechanisms",
"have",
"replaced",
"recurrent",
"neural",
"networks",
"and",
"its",
"variants",
"for",
"machine",
"translation",
"tasks.",
"Transformer",
"using",
"attention",
"mechanism",
"solely",
"achieved",
"state-of-the-art",
"results",
"in",
"sequence",
"modeling.",
"Neural",
"machine",
"translation",
"based",
"on",
"the",
"attention",
"mechanism",
"is",
"parallelizable",
"and",
"addresses",
"the",
"problem",
"of",
"handling",
"long-range",
"dependencies",
"among",
"words",
"in",
"sentences",
"more",
"effectively",
"than",
"recurrent",
"neural",
"networks.",
"One",
"of",
"the",
"key",
"concepts",
"in",
"attention",
"is",
"to",
"learn",
"three",
"matrices,",
"query,",
"key,",
"and",
"value,",
"where",
"global",
"dependencies",
"among",
"words",
"are",
"learned",
"through",
"linearly",
"projecting",
"word",
"embeddings",
"through",
"these",
"matrices.",
"Multiple",
"query,",
"key,",
"value",
"matrices",
"can",
"be",
"learned",
"simultaneously",
"focusing",
"on",
"a",
"different",
"subspace",
"of",
"the",
"embedded",
"dimension,",
"which",
"is",
"called",
"multi-head",
"in",
"Transformer",
".",
"We",
"argue",
"that",
"certain",
"dependencies",
"among",
"words",
"could",
"be",
"learned",
"better",
"through",
"an",
"intermediate",
"context",
"than",
"directly",
"modeling",
"word-word",
"dependencies.",
"This",
"could",
"happen",
"due",
"to",
"the",
"nature",
"of",
"certain",
"dependencies",
"or",
"lack",
"of",
"patterns",
"that",
"lend",
"them",
"difficult",
"to",
"be",
"modeled",
"globally",
"using",
"multi-head",
"self-attention.",
"In",
"this",
"work,",
"we",
"propose",
"a",
"new",
"way",
"of",
"learning",
"dependencies",
"through",
"a",
"context",
"in",
"multi-head",
"using",
"convolution.",
"This",
"new",
"form",
"of",
"multi-head",
"attention",
"along",
"with",
"the",
"traditional",
"form",
"achieves",
"better",
"results",
"than",
"Transformer",
"on",
"the",
"WMT",
"2014",
"English-to-German",
"and",
"English-to-French",
"translation",
"tasks.",
"We",
"also",
"introduce",
"a",
"framework",
"to",
"learn",
"POS",
"tagging",
"and",
"NER",
"information",
"during",
"the",
"training",
"of",
"encoder",
"which",
"further",
"improves",
"results",
"achieving",
"a",
"new",
"state-of-the-art",
"of",
"32.1",
"BLEU,",
"better",
"than",
"existing",
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"We",
"call",
"this",
"Transformer",
"++."
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"studies,",
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"about",
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"experiments",
"on",
"two",
"datasets,",
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"and",
"Tiny",
"Imagenet,",
"present",
"that",
"the",
"proposed",
"method",
"definitely",
"outperforms",
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"and",
"be",
"applicable",
"to",
"other",
"models",
"and",
"datasets."
] |
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[
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"Language",
"Understanding",
"(NLU).",
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"filling",
"and",
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"single",
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"case),",
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"components",
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"monolingual,",
"reducing",
"development",
"and",
"maintenance",
"cost.",
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"are",
"given",
"using",
"the",
"multilingual",
"BART",
"model",
"(Liu",
"et",
"al.,",
"2020)",
"fine-tuned",
"on",
"7",
"languages",
"using",
"the",
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"dataset.",
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"translation",
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"performed,",
"mBART",
"{'}s",
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"comparable",
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"art",
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"BERT",
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"Xu",
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"al.",
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"tested,",
"with",
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"average",
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"95.50{\\%})",
"but",
"worse",
"average",
"slot",
"F1",
"(89.87{\\%}",
"versus",
"90.81{\\%}).",
"When",
"simultaneous",
"translation",
"is",
"performed,",
"average",
"intent",
"classification",
"accuracy",
"degrades",
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"1.7{\\%}",
"relative",
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"slot",
"F1",
"degrades",
"by",
"only",
"1.2{\\%}",
"relative."
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".",
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"QJP",
"and",
"its",
"ana",
"-RRB-",
"ysis",
"results",
"as",
"a",
"base",
"and",
"adding",
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"documents",
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"a",
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"can",
"be",
"developed",
"on",
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"on",
"PCs",
"."
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"Negation",
"is",
"a",
"core",
"construction",
"in",
"natural",
"language.",
"Despite",
"being",
"very",
"successful",
"on",
"many",
"tasks,",
"state-of-the-art",
"pre-trained",
"language",
"models",
"often",
"handle",
"negation",
"incorrectly.",
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"improve",
"language",
"models",
"in",
"this",
"regard,",
"we",
"propose",
"to",
"augment",
"the",
"language",
"modeling",
"objective",
"with",
"an",
"unlikelihood",
"objective",
"that",
"is",
"based",
"on",
"negated",
"generic",
"sentences",
"from",
"a",
"raw",
"text",
"corpus.",
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"training",
"BERT",
"with",
"the",
"resulting",
"combined",
"objective",
"we",
"reduce",
"the",
"mean",
"top~1",
"error",
"rate",
"to",
"4%",
"on",
"the",
"negated",
"LAMA",
"dataset.",
"We",
"also",
"see",
"some",
"improvements",
"on",
"the",
"negated",
"NLI",
"benchmarks."
] |
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"Existing",
"Earth",
"Vision",
"datasets",
"are",
"either",
"suitable",
"for",
"semantic",
"segmentation",
"or",
"object",
"detection.",
"In",
"this",
"work,",
"we",
"introduce",
"the",
"first",
"benchmark",
"dataset",
"for",
"instance",
"segmentation",
"in",
"aerial",
"imagery",
"that",
"combines",
"instance-level",
"object",
"detection",
"and",
"pixel-level",
"segmentation",
"tasks.",
"In",
"comparison",
"to",
"instance",
"segmentation",
"in",
"natural",
"scenes,",
"aerial",
"images",
"present",
"unique",
"challenges",
"e.g.,",
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"huge",
"number",
"of",
"instances",
"per",
"image,",
"large",
"object-scale",
"variations",
"and",
"abundant",
"tiny",
"objects.",
"Our",
"large-scale",
"and",
"densely",
"annotated",
"Instance",
"Segmentation",
"in",
"Aerial",
"Images",
"Dataset",
"(iSAID)",
"comes",
"with",
"655,451",
"object",
"instances",
"for",
"15",
"categories",
"across",
"2,806",
"high-resolution",
"images.",
"Such",
"precise",
"per-pixel",
"annotations",
"for",
"each",
"instance",
"ensure",
"accurate",
"localization",
"that",
"is",
"essential",
"for",
"detailed",
"scene",
"analysis.",
"Compared",
"to",
"existing",
"small-scale",
"aerial",
"image",
"based",
"instance",
"segmentation",
"datasets,",
"iSAID",
"contains",
"15$\\times$",
"the",
"number",
"of",
"object",
"categories",
"and",
"5$\\times$",
"the",
"number",
"of",
"instances.",
"We",
"benchmark",
"our",
"dataset",
"using",
"two",
"popular",
"instance",
"segmentation",
"approaches",
"for",
"natural",
"images,",
"namely",
"Mask",
"R-CNN",
"and",
"PANet",
".",
"In",
"our",
"experiments",
"we",
"show",
"that",
"direct",
"application",
"of",
"off-the-shelf",
"Mask",
"R-CNN",
"and",
"PANet",
"on",
"aerial",
"images",
"provide",
"suboptimal",
"instance",
"segmentation",
"results,",
"thus",
"requiring",
"specialized",
"solutions",
"from",
"the",
"research",
"community.",
"The",
"dataset",
"is",
"publicly",
"available",
"at:",
"https://captain-whu.github.io/iSAID/index.html"
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"This",
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"our",
"system",
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"SemEval-2020",
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"12",
"on",
"Multilingual",
"Offensive",
"Language",
"Identification",
"in",
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"Media",
"(OffensEval",
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"A",
"for",
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"Greek,",
"Arabic,",
"and",
"Turkish",
"languages.",
"We",
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"fine-tune",
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"and",
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"Bert",
"models",
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"and",
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"respectively.",
"For",
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"English",
"language,",
"we",
"use",
"a",
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"fine-tuned",
"BERT",
"models.",
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"to",
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"data",
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"use",
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"BERT",
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"LIIR",
"achieved",
"rank",
"14/38,",
"18/47,",
"24/86,",
"24/54,",
"and",
"25/40",
"in",
"Greek,",
"Turkish,",
"English,",
"Arabic,",
"and",
"Danish",
"languages,",
"respectively."
] |
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[
"Commonsense",
"is",
"defined",
"as",
"the",
"knowledge",
"that",
"is",
"shared",
"by",
"everyone.",
"However,",
"certain",
"types",
"of",
"commonsense",
"knowledge",
"are",
"correlated",
"with",
"culture",
"and",
"geographic",
"locations",
"and",
"they",
"are",
"only",
"shared",
"locally.",
"For",
"example,",
"the",
"scenarios",
"of",
"wedding",
"ceremonies",
"vary",
"across",
"regions",
"due",
"to",
"different",
"customs",
"influenced",
"by",
"historical",
"and",
"religious",
"factors.",
"Such",
"regional",
"characteristics,",
"however,",
"are",
"generally",
"omitted",
"in",
"prior",
"work.",
"In",
"this",
"paper,",
"we",
"construct",
"a",
"Geo-Diverse",
"Visual",
"Commonsense",
"Reasoning",
"dataset",
"(GD-VCR)",
"to",
"test",
"vision-and-language",
"models'",
"ability",
"to",
"understand",
"cultural",
"and",
"geo-location-specific",
"commonsense.",
"In",
"particular,",
"we",
"study",
"two",
"state-of-the-art",
"Vision-and-Language",
"models,",
"VisualBERT",
"and",
"ViLBERT",
"trained",
"on",
"VCR,",
"a",
"standard",
"multimodal",
"commonsense",
"benchmark",
"with",
"images",
"primarily",
"from",
"Western",
"regions.",
"We",
"then",
"evaluate",
"how",
"well",
"the",
"trained",
"models",
"can",
"generalize",
"to",
"answering",
"the",
"questions",
"in",
"GD-VCR.",
"We",
"find",
"that",
"the",
"performance",
"of",
"both",
"models",
"for",
"non-Western",
"regions",
"including",
"East",
"Asia,",
"South",
"Asia,",
"and",
"Africa",
"is",
"significantly",
"lower",
"than",
"that",
"for",
"Western",
"region.",
"We",
"analyze",
"the",
"reasons",
"behind",
"the",
"performance",
"disparity",
"and",
"find",
"that",
"the",
"performance",
"gap",
"is",
"larger",
"on",
"QA",
"pairs",
"that:",
"1)",
"are",
"concerned",
"with",
"culture-related",
"scenarios,",
"e.g.,",
"weddings,",
"religious",
"activities,",
"and",
"festivals;",
"2)",
"require",
"high-level",
"geo-diverse",
"commonsense",
"reasoning",
"rather",
"than",
"low-order",
"perception",
"and",
"recognition.",
"Dataset",
"and",
"code",
"are",
"released",
"at",
"https://github.com/WadeYin9712/GD-VCR."
] |
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[
"We",
"study",
"the",
"optimization",
"aspects",
"of",
"personalized",
"Federated",
"Learning",
"(FL).",
"We",
"propose",
"general",
"optimizers",
"that",
"can",
"be",
"used",
"to",
"solve",
"essentially",
"any",
"existing",
"personalized",
"FL",
"objective,",
"namely",
"a",
"tailored",
"variant",
"of",
"Local",
"SGD",
"and",
"variants",
"of",
"accelerated",
"coordinate",
"descent/accelerated",
"SVRCD.",
"By",
"studying",
"a",
"general",
"personalized",
"objective",
"that",
"is",
"capable",
"of",
"recovering",
"essentially",
"any",
"existing",
"personalized",
"FL",
"objective",
"as",
"a",
"special",
"case,",
"we",
"develop",
"a",
"universal",
"optimization",
"theory",
"applicable",
"to",
"all",
"strongly",
"convex",
"personalized",
"FL",
"models",
"in",
"the",
"literature.",
"We",
"demonstrate",
"the",
"practicality",
"and/or",
"optimality",
"of",
"our",
"methods",
"both",
"in",
"terms",
"of",
"communication",
"and",
"local",
"computation.",
"Surprisingly",
"enough,",
"our",
"general",
"optimization",
"solvers",
"and",
"theory",
"are",
"capable",
"of",
"recovering",
"best-known",
"communication",
"and",
"computation",
"guarantees",
"for",
"solving",
"specific",
"personalized",
"FL",
"objectives.",
"Thus,",
"our",
"proposed",
"methods",
"can",
"be",
"taken",
"as",
"universal",
"optimizers",
"that",
"make",
"the",
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"of",
"task-specific",
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"in",
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"Online",
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"process",
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"time",
"seriessignature",
"data",
"which",
"is",
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"device.",
"Unlikeoffline",
"signature",
"images,",
"the",
"online",
"signature",
"image",
"data",
"consists",
"of",
"pointsthat",
"are",
"arranged",
"in",
"a",
"sequence",
"of",
"time.",
"The",
"aim",
"of",
"this",
"research",
"is",
"to",
"developan",
"improved",
"approach",
"to",
"map",
"the",
"strokes",
"in",
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"test",
"and",
"reference",
"signatures.Current",
"methods",
"make",
"use",
"of",
"the",
"Dynamic",
"Time",
"Warping",
"(DTW",
")",
"algorithm",
"and",
"itsvariant",
"to",
"segment",
"them",
"before",
"comparing",
"each",
"of",
"its",
"data",
"dimension.",
"This",
"paperpresents",
"a",
"modified",
"DTW",
"algorithm",
"with",
"the",
"proposed",
"Lost",
"Box",
"Recovery",
"Algorithmaims",
"to",
"improve",
"the",
"mapping",
"performance",
"for",
"online",
"signature",
"verification"
] |
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[
"Entity",
"mentions",
"embedded",
"in",
"longer",
"entity",
"mentions",
"are",
"referred",
"to",
"as",
"nested",
"entities.",
"Most",
"named",
"entity",
"recognition",
"(NER",
")",
"systems",
"deal",
"only",
"with",
"the",
"flat",
"entities",
"and",
"ignore",
"the",
"inner",
"nested",
"ones,",
"which",
"fails",
"to",
"capture",
"finer-grained",
"semantic",
"information",
"in",
"underlying",
"texts.",
"To",
"address",
"this",
"issue,",
"we",
"propose",
"a",
"novel",
"neural",
"model",
"to",
"identify",
"nested",
"entities",
"by",
"dynamically",
"stacking",
"flat",
"NER",
"layers.",
"Each",
"flat",
"NER",
"layer",
"is",
"based",
"on",
"the",
"state-of-the-art",
"flat",
"NER",
"model",
"that",
"captures",
"sequential",
"context",
"representation",
"with",
"bidirectional",
"Long",
"Short-Term",
"Memory",
"(LSTM",
")",
"layer",
"and",
"feeds",
"it",
"to",
"the",
"cascaded",
"CRF",
"layer.",
"Our",
"model",
"merges",
"the",
"output",
"of",
"the",
"LSTM",
"layer",
"in",
"the",
"current",
"flat",
"NER",
"layer",
"to",
"build",
"new",
"representation",
"for",
"detected",
"entities",
"and",
"subsequently",
"feeds",
"them",
"into",
"the",
"next",
"flat",
"NER",
"layer.",
"This",
"allows",
"our",
"model",
"to",
"extract",
"outer",
"entities",
"by",
"taking",
"full",
"advantage",
"of",
"information",
"encoded",
"in",
"their",
"corresponding",
"inner",
"entities,",
"in",
"an",
"inside-to-outside",
"way.",
"Our",
"model",
"dynamically",
"stacks",
"the",
"flat",
"NER",
"layers",
"until",
"no",
"outer",
"entities",
"are",
"extracted.",
"Extensive",
"evaluation",
"shows",
"that",
"our",
"dynamic",
"model",
"outperforms",
"state-of-the-art",
"feature-based",
"systems",
"on",
"nested",
"NER",
",",
"achieving",
"74.7{\\%}",
"and",
"72.2{\\%}",
"on",
"GENIA",
"and",
"ACE2005",
"datasets,",
"respectively,",
"in",
"terms",
"of",
"F-score."
] |
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[
"The",
"goal",
"of",
"No-Reference",
"Image",
"Quality",
"Assessment",
"(NR-IQA)",
"is",
"to",
"estimate",
"the",
"perceptual",
"image",
"quality",
"in",
"accordance",
"with",
"subjective",
"evaluations,",
"it",
"is",
"a",
"complex",
"and",
"unsolved",
"problem",
"due",
"to",
"the",
"absence",
"of",
"the",
"pristine",
"reference",
"image.",
"In",
"this",
"paper,",
"we",
"propose",
"a",
"novel",
"model",
"to",
"address",
"the",
"NR-IQA",
"task",
"by",
"leveraging",
"a",
"hybrid",
"approach",
"that",
"benefits",
"from",
"Convolutional",
"Neural",
"Networks",
"(CNNs)",
"and",
"self-attention",
"mechanism",
"in",
"Transformer",
"s",
"to",
"extract",
"both",
"local",
"and",
"non-local",
"features",
"from",
"the",
"input",
"image.",
"We",
"capture",
"local",
"structure",
"information",
"of",
"the",
"image",
"via",
"CNNs,",
"then",
"to",
"circumvent",
"the",
"locality",
"bias",
"among",
"the",
"extracted",
"CNNs",
"features",
"and",
"obtain",
"a",
"non-local",
"representation",
"of",
"the",
"image,",
"we",
"utilize",
"Transformer",
"s",
"on",
"the",
"extracted",
"features",
"where",
"we",
"model",
"them",
"as",
"a",
"sequential",
"input",
"to",
"the",
"Transformer",
"model.",
"Furthermore,",
"to",
"improve",
"the",
"monotonicity",
"correlation",
"between",
"the",
"subjective",
"and",
"objective",
"scores,",
"we",
"utilize",
"the",
"relative",
"distance",
"information",
"among",
"the",
"images",
"within",
"each",
"batch",
"and",
"enforce",
"the",
"relative",
"ranking",
"among",
"them.",
"Last",
"but",
"not",
"least,",
"we",
"observe",
"that",
"the",
"performance",
"of",
"NR-IQA",
"models",
"degrades",
"when",
"we",
"apply",
"equivariant",
"transformations",
"(e.g.",
"horizontal",
"flipping)",
"to",
"the",
"inputs.",
"Therefore,",
"we",
"propose",
"a",
"method",
"that",
"leverages",
"self-consistency",
"as",
"a",
"source",
"of",
"self-supervision",
"to",
"improve",
"the",
"robustness",
"of",
"NRIQA",
"models.",
"Specifically,",
"we",
"enforce",
"self-consistency",
"between",
"the",
"outputs",
"of",
"our",
"quality",
"assessment",
"model",
"for",
"each",
"image",
"and",
"its",
"transformation",
"(horizontally",
"flipped)",
"to",
"utilize",
"the",
"rich",
"self-supervisory",
"information",
"and",
"reduce",
"the",
"uncertainty",
"of",
"the",
"model.",
"To",
"demonstrate",
"the",
"effectiveness",
"of",
"our",
"work,",
"we",
"evaluate",
"it",
"on",
"seven",
"standard",
"IQA",
"datasets",
"(both",
"synthetic",
"and",
"authentic)",
"and",
"show",
"that",
"our",
"model",
"achieves",
"state-of-the-art",
"results",
"on",
"various",
"datasets."
] |
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"a",
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"learner",
"data,",
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"of",
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"To",
"make",
"sure",
"the",
"dataset",
"can",
"be",
"freely",
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"the",
"GDPR",
"regulations,",
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"metadata",
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"learners,",
"keeping",
"for",
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"sentence",
"only",
"information",
"about",
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"tongue",
"and",
"the",
"level",
"of",
"the",
"course",
"where",
"the",
"essay",
"has",
"been",
"written.",
"We",
"use",
"the",
"normalized",
"version",
"of",
"learner",
"language",
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"the",
"basis",
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"sentences,",
"and",
"keep",
"only",
"one",
"error",
"per",
"sentence.",
"We",
"repeat",
"the",
"same",
"sentence",
"for",
"each",
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"correction",
"tag",
"used",
"in",
"the",
"sentence.",
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"1",
"we",
"have",
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"categories",
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"available",
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"SweLL),",
"all",
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"to",
"lexical",
"or",
"word-building",
"choices.",
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"baseline",
"results",
"for",
"the",
"binary",
"classification",
"show",
"an",
"accuracy",
"of",
"58%",
"for",
"DaLAJ",
"1",
"using",
"BERT",
"embeddings.",
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"(Swe.",
"SuperLim)",
"benchmark.",
"Below,",
"we",
"describe",
"the",
"format",
"of",
"the",
"dataset,",
"first",
"experiments,",
"our",
"insights",
"and",
"the",
"motivation",
"for",
"the",
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"approach",
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"data",
"sharing."
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"The",
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"pandemic",
"has",
"led",
"to",
"a",
"devastating",
"effect",
"on",
"the",
"global",
"public",
"health.",
"Computed",
"Tomography",
"(CT)",
"is",
"an",
"effective",
"tool",
"in",
"the",
"screening",
"of",
"COVID-19.",
"It",
"is",
"of",
"great",
"importance",
"to",
"rapidly",
"and",
"accurately",
"segment",
"COVID-19",
"from",
"CT",
"to",
"help",
"diagnostic",
"and",
"patient",
"monitoring.",
"In",
"this",
"paper,",
"we",
"propose",
"a",
"U-Net",
"based",
"segmentation",
"network",
"using",
"attention",
"mechanism.",
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"not",
"all",
"the",
"features",
"extracted",
"from",
"the",
"encoders",
"are",
"useful",
"for",
"segmentation,",
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"propose",
"to",
"incorporate",
"an",
"attention",
"mechanism",
"including",
"a",
"spatial",
"and",
"a",
"channel",
"attention,",
"to",
"a",
"U-Net",
"architecture",
"to",
"re-weight",
"the",
"feature",
"representation",
"spatially",
"and",
"channel-wise",
"to",
"capture",
"rich",
"contextual",
"relationships",
"for",
"better",
"feature",
"representation.",
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"addition,",
"the",
"focal",
"tversky",
"loss",
"is",
"introduced",
"to",
"deal",
"with",
"small",
"lesion",
"segmentation.",
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"experiment",
"results,",
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"on",
"a",
"COVID-19",
"CT",
"segmentation",
"dataset",
"where",
"473",
"CT",
"slices",
"are",
"available,",
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"the",
"proposed",
"method",
"can",
"achieve",
"an",
"accurate",
"and",
"rapid",
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"on",
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"segmentation.",
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"method",
"takes",
"only",
"0.29",
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"a",
"single",
"CT",
"slice.",
"The",
"obtained",
"Dice",
"Score,",
"Sensitivity",
"and",
"Specificity",
"are",
"83.1%,",
"86.70%",
"and",
"99.3%,",
"respectively."
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"present",
"a",
"vector",
"space",
"model",
"that",
"supports",
"the",
"computation",
"of",
"appropriate",
"vector",
"representations",
"for",
"words",
"in",
"context",
",",
"and",
"apply",
"it",
"to",
"a",
"paraphrase",
"ranking",
"task",
".",
"An",
"evaluation",
"on",
"the",
"SemEval",
"2007",
"lexical",
"substitution",
"task",
"data",
"shows",
"promising",
"results",
":",
"the",
"model",
"significantly",
"outperforms",
"a",
"current",
"state",
"of",
"the",
"art",
"model",
",",
"and",
"our",
"treatment",
"of",
"context",
"is",
"effective",
"."
] |
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"availability",
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"sensors",
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"can",
"acquire",
"sequential",
"data",
"over",
"time.",
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"Activity",
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"one",
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"fields",
"which",
"are",
"actively",
"benefiting",
"from",
"this",
"availability.",
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"most",
"of",
"the",
"approaches",
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"by",
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"predefined",
"activity",
"classes,",
"this",
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"a",
"novel",
"approach",
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"sequential",
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"end,",
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"used",
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"analysis.",
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"make",
"the",
"data",
"suitable",
"for",
"LDA",
",",
"we",
"extract",
"the",
"so-called",
"sensory\tO\nwords",
"from",
"the",
"sequential",
"data.",
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"carried",
"out",
"experiments",
"on",
"a",
"challenging",
"HAR",
"dataset,",
"demonstrating",
"that",
"LDA",
"is",
"capable",
"of",
"uncovering",
"underlying",
"structures",
"in",
"sequential",
"data,",
"which",
"provide",
"a",
"human-understandable",
"representation",
"of",
"the",
"data.",
"The",
"extrinsic",
"evaluations",
"reveal",
"that",
"LDA",
"is",
"capable",
"of",
"accurately",
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"HAR",
"data",
"sequences",
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"the",
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"A",
"micro-sleep",
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"sleep",
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"detection",
"during",
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"is",
"crucial",
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"prevent",
"accidents",
"that",
"could",
"claim",
"a",
"lot",
"of",
"people's",
"lives.",
"Electroencephalogram",
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"is",
"suitable",
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"detect",
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"learning",
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"brain",
"states,",
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"data",
"should",
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"needed.",
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"micro-sleep",
"data",
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"data",
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"home",
"is",
"easier",
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"learning",
"approach",
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"EEG",
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"performance",
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"sleep",
"stages",
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[
"While",
"it",
"has",
"been",
"shown",
"that",
"Neural",
"Machine",
"Translation",
"(NMT)",
"is",
"highly",
"sensitive",
"to",
"noisy",
"parallel",
"training",
"samples,",
"prior",
"work",
"treats",
"all",
"types",
"of",
"mismatches",
"between",
"source",
"and",
"target",
"as",
"noise.",
"As",
"a",
"result,",
"it",
"remains",
"unclear",
"how",
"samples",
"that",
"are",
"mostly",
"equivalent",
"but",
"contain",
"a",
"small",
"number",
"of",
"semantically",
"divergent",
"tokens",
"impact",
"NMT",
"training.",
"To",
"close",
"this",
"gap,",
"we",
"analyze",
"the",
"impact",
"of",
"different",
"types",
"of",
"fine-grained",
"semantic",
"divergences",
"on",
"Transformer",
"models.",
"We",
"show",
"that",
"models",
"trained",
"on",
"synthetic",
"divergences",
"output",
"degenerated",
"text",
"more",
"frequently",
"and",
"are",
"less",
"confident",
"in",
"their",
"predictions.",
"Based",
"on",
"these",
"findings,",
"we",
"introduce",
"a",
"divergent-aware",
"NMT",
"framework",
"that",
"uses",
"factors",
"to",
"help",
"NMT",
"recover",
"from",
"the",
"degradation",
"caused",
"by",
"naturally",
"occurring",
"divergences,",
"improving",
"both",
"translation",
"quality",
"and",
"model",
"calibration",
"on",
"EN-FR",
"tasks."
] |
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[
"Accurately",
"ranking",
"the",
"vast",
"number",
"of",
"candidate",
"detections",
"is",
"crucial",
"for",
"dense",
"object",
"detectors",
"to",
"achieve",
"high",
"performance.",
"Prior",
"work",
"uses",
"the",
"classification",
"score",
"or",
"a",
"combination",
"of",
"classification",
"and",
"predicted",
"localization",
"scores",
"to",
"rank",
"candidates.",
"However,",
"neither",
"option",
"results",
"in",
"a",
"reliable",
"ranking,",
"thus",
"degrading",
"detection",
"performance.",
"In",
"this",
"paper,",
"we",
"propose",
"to",
"learn",
"an",
"Iou-aware",
"Classification",
"Score",
"(IACS)",
"as",
"a",
"joint",
"representation",
"of",
"object",
"presence",
"confidence",
"and",
"localization",
"accuracy.",
"We",
"show",
"that",
"dense",
"object",
"detectors",
"can",
"achieve",
"a",
"more",
"accurate",
"ranking",
"of",
"candidate",
"detections",
"based",
"on",
"the",
"IACS.",
"We",
"design",
"a",
"new",
"loss",
"function,",
"named",
"Varifocal",
"Loss,",
"to",
"train",
"a",
"dense",
"object",
"detector",
"to",
"predict",
"the",
"IACS,",
"and",
"propose",
"a",
"new",
"star-shaped",
"bounding",
"box",
"feature",
"representation",
"for",
"IACS",
"prediction",
"and",
"bounding",
"box",
"refinement.",
"Combining",
"these",
"two",
"new",
"components",
"and",
"a",
"bounding",
"box",
"refinement",
"branch,",
"we",
"build",
"an",
"IoU-aware",
"dense",
"object",
"detector",
"based",
"on",
"the",
"FCOS+ATSS",
"architecture,",
"that",
"we",
"call",
"VarifocalNet",
"or",
"VFNet",
"for",
"short.",
"Extensive",
"experiments",
"on",
"MS",
"COCO",
"show",
"that",
"our",
"VFNet",
"consistently",
"surpasses",
"the",
"strong",
"baseline",
"by",
"$\\sim$2.0",
"AP",
"with",
"different",
"backbones.",
"Our",
"best",
"model",
"VFNet",
"#NAME?",
"with",
"Res2Net-101-DCN",
"achieves",
"a",
"single-model",
"single-scale",
"AP",
"of",
"55.1",
"on",
"COCO",
"test-dev,",
"which",
"is",
"state-of-the-art",
"among",
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"object",
"detectors.Code",
"is",
"available",
"at",
"https://github.com/hyz-xmaster/VarifocalNet",
"."
] |
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[
"Sequential",
"matching",
"using",
"hand-crafted",
"heuristics",
"has",
"been",
"standard",
"practice",
"in",
"route-based",
"place",
"recognition",
"for",
"enhancing",
"pairwise",
"similarity",
"results",
"for",
"nearly",
"a",
"decade.",
"However,",
"precision-recall",
"performance",
"of",
"these",
"algorithms",
"dramatically",
"degrades",
"when",
"searching",
"on",
"short",
"temporal",
"window",
"(TW)",
"lengths,",
"while",
"demanding",
"high",
"compute",
"and",
"storage",
"costs",
"on",
"large",
"robotic",
"datasets",
"for",
"autonomous",
"navigation",
"research.",
"Here,",
"influenced",
"by",
"biological",
"systems",
"that",
"robustly",
"navigate",
"spacetime",
"scales",
"even",
"without",
"vision,",
"we",
"develop",
"a",
"joint",
"visual",
"and",
"positional",
"representation",
"learning",
"technique,",
"via",
"a",
"sequential",
"process,",
"and",
"design",
"a",
"learning-based",
"CNN+LSTM",
"architecture,",
"trainable",
"via",
"backpropagation",
"through",
"time,",
"for",
"viewpoint-",
"and",
"appearance-invariant",
"place",
"recognition.",
"Our",
"approach,",
"Sequential",
"Place",
"Learning",
"(SPL),",
"is",
"based",
"on",
"a",
"CNN",
"function",
"that",
"visually",
"encodes",
"an",
"environment",
"from",
"a",
"single",
"traversal,",
"thus",
"reducing",
"storage",
"capacity,",
"while",
"an",
"LSTM",
"temporally",
"fuses",
"each",
"visual",
"embedding",
"with",
"corresponding",
"positional",
"data",
"--",
"obtained",
"from",
"any",
"source",
"of",
"motion",
"estimation",
"--",
"for",
"direct",
"sequential",
"inference.",
"Contrary",
"to",
"classical",
"two-stage",
"pipelines,",
"e.g.,",
"match-then-temporally-filter,",
"our",
"network",
"directly",
"eliminates",
"false-positive",
"rates",
"while",
"jointly",
"learning",
"sequence",
"matching",
"from",
"a",
"single",
"monocular",
"image",
"sequence,",
"even",
"using",
"short",
"TWs.",
"Hence,",
"we",
"demonstrate",
"that",
"our",
"model",
"outperforms",
"15",
"classical",
"methods",
"while",
"setting",
"new",
"state-of-the-art",
"performance",
"standards",
"on",
"4",
"challenging",
"benchmark",
"datasets,",
"where",
"one",
"of",
"them",
"can",
"be",
"considered",
"solved",
"with",
"recall",
"rates",
"of",
"100%",
"at",
"100%",
"precision,",
"correctly",
"matching",
"all",
"places",
"under",
"extreme",
"sunlight-darkness",
"changes.",
"In",
"addition,",
"we",
"show",
"that",
"SPL",
"can",
"be",
"up",
"to",
"70x",
"faster",
"to",
"deploy",
"than",
"classical",
"methods",
"on",
"a",
"729",
"km",
"route",
"comprising",
"35,768",
"consecutive",
"frames.",
"Extensive",
"experiments",
"demonstrate",
"the...",
"Baseline",
"code",
"available",
"at",
"https://github.com/mchancan/deepseqslam"
] |
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[
"Contextualized",
"word",
"embeddings",
"derived",
"from",
"pre-trained",
"language",
"models",
"(LMs)show",
"significant",
"improvements",
"on",
"downstream",
"NLP",
"tasks.",
"Pre-training",
"ondomain-specific",
"corpora,",
"such",
"as",
"biomedical",
"articles,",
"further",
"improves",
"theirperformance.",
"In",
"this",
"paper,",
"we",
"conduct",
"probing",
"experiments",
"to",
"determine",
"whatadditional",
"information",
"is",
"carried",
"intrinsically",
"by",
"the",
"in-domain",
"trainedcontextualized",
"embeddings.",
"For",
"this",
"we",
"use",
"the",
"pre-trained",
"LMs",
"as",
"fixed",
"featureextractors",
"and",
"restrict",
"the",
"downstream",
"task",
"models",
"to",
"not",
"have",
"additionalsequence",
"modeling",
"layers.",
"We",
"compare",
"BERT,",
"ELMo",
",",
"BioBERT",
"and",
"BioELMo",
",",
"abiomedical",
"version",
"of",
"ELMo",
"trained",
"on",
"10M",
"PubMed",
"abstracts.",
"Surprisingly,",
"whilefine-tuned",
"BioBERT",
"is",
"better",
"than",
"BioELMo",
"in",
"biomedical",
"NER",
"and",
"NLI",
"tasks,",
"as",
"afixed",
"feature",
"extractor",
"BioELMo",
"outperforms",
"BioBERT",
"in",
"our",
"probing",
"tasks.",
"Weuse",
"visualization",
"and",
"nearest",
"neighbor",
"analysis",
"to",
"show",
"that",
"better",
"encoding",
"ofentity-type",
"and",
"relational",
"information",
"leads",
"to",
"this",
"superiority."
] |
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[
"In",
"this",
"work,",
"we",
"focus",
"on",
"the",
"problem",
"of",
"entity",
"alignment",
"in",
"Knowledge",
"Graphs",
"(KG)",
"and",
"we",
"report",
"on",
"our",
"experiences",
"when",
"applying",
"a",
"Graph",
"Convolutional",
"Network",
"(GCN",
")",
"based",
"model",
"for",
"this",
"task.",
"Variants",
"of",
"GCN",
"are",
"used",
"in",
"multiple",
"state-of-the-art",
"approaches",
"and",
"therefore",
"it",
"is",
"important",
"to",
"understand",
"the",
"specifics",
"and",
"limitations",
"of",
"GCN",
"#NAME?",
"models.",
"Despite",
"serious",
"efforts,",
"we",
"were",
"not",
"able",
"to",
"fully",
"reproduce",
"the",
"results",
"from",
"the",
"original",
"paper",
"and",
"after",
"a",
"thorough",
"audit",
"of",
"the",
"code",
"provided",
"by",
"authors,",
"we",
"concluded,",
"that",
"their",
"implementation",
"is",
"different",
"from",
"the",
"architecture",
"described",
"in",
"the",
"paper.",
"In",
"addition,",
"several",
"tricks",
"are",
"required",
"to",
"make",
"the",
"model",
"work",
"and",
"some",
"of",
"them",
"are",
"not",
"very",
"intuitive.",
"We",
"provide",
"an",
"extensive",
"ablation",
"study",
"to",
"quantify",
"the",
"effects",
"these",
"tricks",
"and",
"changes",
"of",
"architecture",
"have",
"on",
"final",
"performance.",
"Furthermore,",
"we",
"examine",
"current",
"evaluation",
"approaches",
"and",
"systematize",
"available",
"benchmark",
"datasets.",
"We",
"believe",
"that",
"people",
"interested",
"in",
"KG",
"matching",
"might",
"profit",
"from",
"our",
"work,",
"as",
"well",
"as",
"novices",
"entering",
"the",
"field"
] |
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[
"In",
"this",
"paper,",
"we",
"summarize",
"the",
"application",
"of",
"transformer",
"and",
"its",
"streamable",
"variant,",
"Emformer",
"based",
"acoustic",
"model",
"for",
"large",
"scale",
"speech",
"recognition",
"applications.",
"We",
"compare",
"the",
"transformer",
"based",
"acoustic",
"models",
"with",
"their",
"LSTM",
"counterparts",
"on",
"industrial",
"scale",
"tasks.",
"Specifically,",
"we",
"compare",
"Emformer",
"with",
"latency-controlled",
"BLSTM",
"(LCBLSTM",
")",
"on",
"medium",
"latency",
"tasks",
"and",
"LSTM",
"on",
"low",
"latency",
"tasks.",
"On",
"a",
"low",
"latency",
"voice",
"assistant",
"task,",
"Emformer",
"gets",
"24%",
"to",
"26%",
"relative",
"word",
"error",
"rate",
"reductions",
"(WERRs).",
"For",
"medium",
"latency",
"scenarios,",
"comparing",
"with",
"LCBLSTM",
"with",
"similar",
"model",
"size",
"and",
"latency,",
"Emformer",
"gets",
"significant",
"WERR",
"across",
"four",
"languages",
"in",
"video",
"captioning",
"datasets",
"with",
"03-Feb",
"times",
"inference",
"real-time",
"factors",
"reduction."
] |
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[
"Nowadays,",
"multi-sensor",
"technologies",
"are",
"applied",
"in",
"many",
"fields,",
"e.g.,",
"Health",
"Care",
"(HC),",
"Human",
"Activity",
"Recognition",
"(HAR),",
"and",
"Industrial",
"Control",
"System",
"(ICS).",
"These",
"sensors",
"can",
"generate",
"a",
"substantial",
"amount",
"of",
"multivariate",
"time-series",
"data.",
"Unsupervised",
"anomaly",
"detection",
"on",
"multi-sensor",
"time-series",
"data",
"has",
"been",
"proven",
"critical",
"in",
"machine",
"learning",
"researches.",
"The",
"key",
"challenge",
"is",
"to",
"discover",
"generalized",
"normal",
"patterns",
"by",
"capturing",
"spatial-temporal",
"correlation",
"in",
"multi-sensor",
"data.",
"Beyond",
"this",
"challenge,",
"the",
"noisy",
"data",
"is",
"often",
"intertwined",
"with",
"the",
"training",
"data,",
"which",
"is",
"likely",
"to",
"mislead",
"the",
"model",
"by",
"making",
"it",
"hard",
"to",
"distinguish",
"between",
"the",
"normal,",
"abnormal,",
"and",
"noisy",
"data.",
"Few",
"of",
"previous",
"researches",
"can",
"jointly",
"address",
"these",
"two",
"challenges.",
"In",
"this",
"paper,",
"we",
"propose",
"a",
"novel",
"deep",
"learning-based",
"anomaly",
"detection",
"algorithm",
"called",
"Deep",
"Convolutional",
"Autoencoding",
"Memory",
"network",
"(CAE-M).",
"We",
"first",
"build",
"a",
"Deep",
"Convolutional",
"Autoencoder",
"to",
"characterize",
"spatial",
"dependence",
"of",
"multi-sensor",
"data",
"with",
"a",
"Maximum",
"Mean",
"Discrepancy",
"(MMD)",
"to",
"better",
"distinguish",
"between",
"the",
"noisy,",
"normal,",
"and",
"abnormal",
"data.",
"Then,",
"we",
"construct",
"a",
"Memory",
"Network",
"consisting",
"of",
"linear",
"(Autoregressive",
"Model)",
"and",
"non-linear",
"predictions",
"(Bidirectional",
"LSTM",
"with",
"Attention)",
"to",
"capture",
"temporal",
"dependence",
"from",
"time-series",
"data.",
"Finally,",
"CAE-M",
"jointly",
"optimizes",
"these",
"two",
"subnetworks.",
"We",
"empirically",
"compare",
"the",
"proposed",
"approach",
"with",
"several",
"state-of-the-art",
"anomaly",
"detection",
"methods",
"on",
"HAR",
"and",
"HC",
"datasets.",
"Experimental",
"results",
"demonstrate",
"that",
"our",
"proposed",
"model",
"outperforms",
"these",
"existing",
"methods."
] |
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[
"Recent",
"advances",
"in",
"deep",
"learning",
"have",
"drastically",
"improved",
"performance",
"on",
"many",
"Natural",
"Language",
"Understanding",
"(NLU)",
"tasks.",
"However,",
"the",
"data",
"used",
"to",
"train",
"NLU",
"models",
"may",
"contain",
"private",
"information",
"such",
"as",
"addresses",
"or",
"phone",
"numbers,",
"particularly",
"when",
"drawn",
"from",
"human",
"subjects.",
"It",
"is",
"desirable",
"that",
"underlying",
"models",
"do",
"not",
"expose",
"private",
"information",
"contained",
"in",
"the",
"training",
"data.",
"Differentially",
"Private",
"Stochastic",
"Gradient",
"Descent",
"(DP-SGD)",
"has",
"been",
"proposed",
"as",
"a",
"mechanism",
"to",
"build",
"privacy-preserving",
"models.",
"However,",
"DP-SGD",
"can",
"be",
"prohibitively",
"slow",
"to",
"train.",
"In",
"this",
"work,",
"we",
"propose",
"a",
"more",
"efficient",
"DP-SGD",
"for",
"training",
"using",
"a",
"GPU",
"infrastructure",
"and",
"apply",
"it",
"to",
"fine-tuning",
"models",
"based",
"on",
"LSTM",
"and",
"transformer",
"architectures.",
"We",
"report",
"faster",
"training",
"times,",
"alongside",
"accuracy,",
"theoretical",
"privacy",
"guarantees",
"and",
"success",
"of",
"Membership",
"inference",
"attacks",
"for",
"our",
"models",
"and",
"observe",
"that",
"fine-tuning",
"with",
"proposed",
"variant",
"of",
"DP-SGD",
"can",
"yield",
"competitive",
"models",
"without",
"significant",
"degradation",
"in",
"training",
"time",
"and",
"improvement",
"in",
"privacy",
"protection.",
"We",
"also",
"make",
"observations",
"such",
"as",
"looser",
"theoretical",
"$\\epsilon,",
"\\delta$",
"can",
"translate",
"into",
"significant",
"practical",
"privacy",
"gains."
] |
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[
"The",
"availability",
"of",
"large",
"parsed",
"corpora",
"and",
"improved",
"computing",
"resources",
"now",
"make",
"it",
"possible",
"to",
"extract",
"vast",
"amounts",
"of",
"lexical",
"data",
".",
"We",
"describe",
"the",
"process",
"of",
"extracting",
"structured",
"data",
"and",
"several",
"methods",
"of",
"deriving",
"argument",
"structure",
"mappings",
"for",
"deverbal",
"nouns",
"that",
"significantly",
"improves",
"upon",
"non-lexicalized",
"rule-based",
"methods",
".",
"For",
"a",
"typical",
"model",
",",
"the",
"F-measure",
"of",
"performance",
"improves",
"from",
"a",
"baseline",
"of",
"about",
"0.72",
"to",
"0.81",
"."
] |
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5,
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] |
[
"We",
"develop",
"a",
"Multimodal",
"Spatiotemporal",
"Neural",
"Fusion",
"network",
"for",
"Multi-Task",
"Learning",
"(MSNF-MTCL)",
"to",
"predict",
"5",
"important",
"students'",
"retention",
"risks:",
"future",
"dropout,",
"next",
"semester",
"dropout,",
"type",
"of",
"dropout,",
"duration",
"of",
"dropout",
"and",
"cause",
"of",
"dropout.",
"First,",
"we",
"develop",
"a",
"general",
"purpose",
"multi-modal",
"neural",
"fusion",
"network",
"model",
"MSNF",
"for",
"learning",
"students'",
"academic",
"information",
"representation",
"by",
"fusing",
"spatial",
"and",
"temporal",
"unstructured",
"advising",
"notes",
"with",
"spatiotemporal",
"structured",
"data.",
"MSNF",
"combines",
"a",
"Bidirectional",
"Encoder",
"Representations",
"from",
"Transformers",
"(BERT)-based",
"document",
"embedding",
"framework",
"to",
"represent",
"each",
"advising",
"note,",
"Long-Short",
"Term",
"Memory",
"(LSTM",
")",
"network",
"to",
"model",
"temporal",
"advising",
"note",
"embeddings,",
"LSTM",
"network",
"to",
"model",
"students'",
"temporal",
"performance",
"variables",
"and",
"students'",
"static",
"demographics",
"altogether.",
"The",
"final",
"fused",
"representation",
"from",
"MSNF",
"has",
"been",
"utilized",
"on",
"a",
"Multi-Task",
"Cascade",
"Learning",
"(MTCL)",
"model",
"towards",
"building",
"MSNF-MTCL",
"for",
"predicting",
"5",
"student",
"retention",
"risks.",
"We",
"evaluate",
"MSNFMTCL",
"on",
"a",
"large",
"educational",
"database",
"consists",
"of",
"36,445",
"college",
"students",
"over",
"18",
"years",
"period",
"of",
"time",
"that",
"provides",
"promising",
"performances",
"comparing",
"with",
"the",
"nearest",
"state-of-art",
"models.",
"Additionally,",
"we",
"test",
"the",
"fairness",
"of",
"such",
"model",
"given",
"the",
"existence",
"of",
"biases."
] |
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[
"Entity",
"alignment",
"aims",
"at",
"integrating",
"complementary",
"knowledge",
"graphs",
"(KGs)",
"from",
"different",
"sources",
"or",
"languages,",
"which",
"may",
"benefit",
"many",
"knowledge-driven",
"applications.",
"It",
"is",
"challenging",
"due",
"to",
"the",
"heterogeneity",
"of",
"KGs",
"and",
"limited",
"seed",
"alignments.",
"In",
"this",
"paper,",
"we",
"propose",
"a",
"semi-supervised",
"entity",
"alignment",
"method",
"by",
"joint",
"Knowledge",
"Embedding",
"model",
"and",
"Cross-Graph",
"model",
"(KECG).",
"It",
"can",
"make",
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"model,",
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"Attention",
"Network",
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")",
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"encode",
"graphs,",
"and",
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"share",
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"transfer",
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"knowledge",
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"to",
"ignore",
"unimportant",
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"for",
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"via",
"attention",
"mechanism.",
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"available",
"datasets",
"as",
"well",
"as",
"further",
"analysis",
"demonstrate",
"the",
"effectiveness",
"of",
"KECG.",
"Our",
"codes",
"can",
"be",
"found",
"in",
"https:",
"//github.com/THU-KEG/KECG."
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[
"As",
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"from",
"large-scale",
"pre-trained",
"models",
"becomes",
"more",
"prevalent",
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"Natural",
"Language",
"Processing",
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"operating",
"these",
"large",
"models",
"in",
"on-the-edge",
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"under",
"constrained",
"computational",
"training",
"or",
"inference",
"budgets",
"remains",
"challenging.",
"In",
"this",
"work,",
"we",
"propose",
"a",
"method",
"to",
"pre-train",
"a",
"smaller",
"general-purpose",
"language",
"representation",
"model,",
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",",
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"then",
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"on",
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"like",
"its",
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"While",
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"prior",
"work",
"investigated",
"the",
"use",
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"building",
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"models,",
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"pre-training",
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"show",
"that",
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"is",
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"size",
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"while",
"retaining",
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"language",
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"and",
"being",
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"faster.",
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"the",
"inductive",
"biases",
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"and",
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"a",
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[
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"networks",
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"reduce",
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"cost,",
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"prior",
"work",
"focuses",
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"studying",
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"changing",
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"network",
"size.",
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"of",
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"networks",
"have",
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"cost",
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"memory",
"budgets,",
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"can",
"be",
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"off",
"with",
"model",
"quality",
"by",
"changing",
"the",
"number",
"of",
"parameters.",
"In",
"this",
"work,",
"we",
"use",
"ResNet",
"as",
"a",
"case",
"study",
"to",
"systematically",
"investigate",
"the",
"effects",
"of",
"quantization",
"on",
"inference",
"compute",
"cost-quality",
"tradeoff",
"curves.",
"Our",
"results",
"suggest",
"that",
"for",
"each",
"bfloat16",
"ResNet",
"model,",
"there",
"are",
"quantized",
"models",
"with",
"lower",
"cost",
"and",
"higher",
"accuracy;",
"in",
"other",
"words,",
"the",
"bfloat16",
"compute",
"cost-quality",
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"and",
"8-bit",
"curves,",
"with",
"models",
"primarily",
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"to",
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"yielding",
"the",
"best",
"Pareto",
"curve.",
"Furthermore,",
"we",
"achieve",
"state-of-the-art",
"results",
"on",
"ImageNet",
"for",
"4-bit",
"ResNet",
"-50",
"with",
"quantization-aware",
"training,",
"obtaining",
"a",
"top-1",
"eval",
"accuracy",
"of",
"77.09%.",
"We",
"demonstrate",
"the",
"regularizing",
"effect",
"of",
"quantization",
"by",
"measuring",
"the",
"generalization",
"gap.",
"The",
"quantization",
"method",
"we",
"used",
"is",
"optimized",
"for",
"practicality:",
"It",
"requires",
"little",
"tuning",
"and",
"is",
"designed",
"with",
"hardware",
"capabilities",
"in",
"mind.",
"Our",
"work",
"motivates",
"further",
"research",
"into",
"optimal",
"numeric",
"formats",
"for",
"quantization,",
"as",
"well",
"as",
"the",
"development",
"of",
"machine",
"learning",
"accelerators",
"supporting",
"these",
"formats.",
"As",
"part",
"of",
"this",
"work,",
"we",
"contribute",
"a",
"quantization",
"library",
"written",
"in",
"JAX,",
"which",
"is",
"open-sourced",
"at",
"https://github.com/google-research/google-research/tree/master/aqt."
] |
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[
"Domain",
"adaptation",
"is",
"an",
"important",
"open",
"problem",
"in",
"deep",
"reinforcement",
"learning(RL).",
"In",
"many",
"scenarios",
"of",
"interest",
"data",
"is",
"hard",
"to",
"obtain,",
"so",
"agents",
"may",
"learna",
"source",
"policy",
"in",
"a",
"setting",
"where",
"data",
"is",
"readily",
"available,",
"with",
"the",
"hopethat",
"it",
"generalises",
"well",
"to",
"the",
"target",
"domain.",
"We",
"propose",
"a",
"new",
"multi-stage",
"RLagent,",
"DARLA",
"(DisentAngled",
"Representation",
"Learning",
"Agent),",
"which",
"learns",
"to",
"seebefore",
"learning",
"to",
"act.",
"DARLA's",
"vision",
"is",
"based",
"on",
"learning",
"a",
"disentangledrepresentation",
"of",
"the",
"observed",
"environment.",
"Once",
"DARLA",
"can",
"see,",
"it",
"is",
"able",
"toacquire",
"source",
"policies",
"that",
"are",
"robust",
"to",
"many",
"domain",
"shifts",
"-",
"even",
"with",
"noaccess",
"to",
"the",
"target",
"domain.",
"DARLA",
"significantly",
"outperforms",
"conventionalbaselines",
"in",
"zero-shot",
"domain",
"adaptation",
"scenarios,",
"an",
"effect",
"that",
"holds",
"acrossa",
"variety",
"of",
"RL",
"environments",
"(Jaco",
"arm,",
"DeepMind",
"Lab)",
"and",
"base",
"RL",
"algorithms(DQN,",
"A3C",
"and",
"EC)."
] |
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[
"Semantic",
"parsing",
"is",
"a",
"challenging",
"task",
"whose",
"purpose",
"is",
"to",
"convert",
"a",
"natural",
"language",
"utterance",
"to",
"machine-understandable",
"information",
"representation.",
"Recently,",
"solutions",
"using",
"Neural",
"Machine",
"Translation",
"have",
"achieved",
"many",
"promising",
"results,",
"especially",
"Transformer",
"because",
"of",
"the",
"ability",
"to",
"learn",
"long-range",
"word",
"dependencies.",
"However,",
"the",
"one",
"drawback",
"of",
"adapting",
"the",
"original",
"Transformer",
"to",
"the",
"semantic",
"parsing",
"is",
"the",
"lack",
"of",
"detail",
"in",
"expressing",
"the",
"information",
"of",
"sentences.",
"Therefore,",
"this",
"work",
"proposes",
"a",
"PhraseTransformer",
"architecture",
"that",
"is",
"capable",
"of",
"a",
"more",
"detailed",
"meaning",
"representation",
"by",
"learning",
"the",
"phrase",
"dependencies",
"in",
"the",
"sentence.",
"The",
"main",
"idea",
"is",
"to",
"incorporate",
"Long",
"Short-Term",
"Memory",
"(LSTM)",
"into",
"the",
"Self-Attention",
"mechanism",
"of",
"the",
"original",
"Transformer",
"to",
"capture",
"more",
"local",
"context",
"of",
"phrases.",
"Experimental",
"results",
"show",
"that",
"the",
"proposed",
"model",
"captures",
"the",
"detailed",
"meaning",
"better",
"than",
"Transformer",
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"competitive",
"performance",
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"Geo,",
"MSParS",
"datasets,",
"and",
"leads",
"to",
"new",
"state-of-the-art",
"(SOTA)",
"performance",
"on",
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"dataset."
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"Architecture",
"search",
"is",
"the",
"automatic",
"process",
"of",
"designing",
"the",
"model",
"or",
"cell",
"structure",
"that",
"is",
"optimal",
"for",
"the",
"given",
"dataset",
"or",
"task.",
"Recently,",
"this",
"approach",
"has",
"shown",
"good",
"improvements",
"in",
"terms",
"of",
"performance",
"(tested",
"on",
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"modeling",
"and",
"image",
"classification)",
"with",
"reasonable",
"training",
"speed",
"using",
"a",
"weight",
"sharing-based",
"approach",
"called",
"Efficient",
"Neural",
"Architecture",
"Search",
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"In",
"this",
"work,",
"we",
"propose",
"a",
"novel",
"architecture",
"search",
"algorithm",
"called",
"Flexible",
"and",
"Expressible",
"Neural",
"Architecture",
"Search",
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"with",
"more",
"flexible",
"and",
"expressible",
"search",
"space",
"than",
"ENAS,",
"in",
"terms",
"of",
"more",
"activation",
"functions,",
"input",
"edges,",
"and",
"atomic",
"operations.",
"Also,",
"our",
"FENAS",
"approach",
"is",
"able",
"to",
"reproduce",
"the",
"well-known",
"LSTM",
"and",
"GRU",
"architectures",
"(unlike",
"ENAS),",
"and",
"is",
"also",
"able",
"to",
"initialize",
"with",
"them",
"for",
"finding",
"architectures",
"more",
"efficiently.",
"We",
"explore",
"this",
"extended",
"search",
"space",
"via",
"evolutionary",
"search",
"and",
"show",
"that",
"FENAS",
"performs",
"significantly",
"better",
"on",
"several",
"popular",
"text",
"classification",
"tasks",
"and",
"performs",
"similar",
"to",
"ENAS",
"on",
"standard",
"language",
"model",
"benchmark.",
"Further,",
"we",
"present",
"ablations",
"and",
"analyses",
"on",
"our",
"FENAS",
"approach."
] |
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[
"Micro-Expression",
"(ME)",
"is",
"the",
"spontaneous,",
"involuntary",
"movement",
"of",
"a",
"face",
"that",
"can",
"reveal",
"the",
"TRUE",
"feeling.",
"Recently,",
"increasing",
"researches",
"have",
"paid",
"attention",
"to",
"this",
"field",
"combing",
"deep",
"learning",
"techniques.",
"Action",
"units",
"(AUs)",
"are",
"the",
"fundamental",
"actions",
"reflecting",
"the",
"facial",
"muscle",
"movements",
"and",
"AU",
"detection",
"has",
"been",
"adopted",
"by",
"many",
"researches",
"to",
"classify",
"facial",
"expressions.",
"However,",
"the",
"time-consuming",
"annotation",
"process",
"makes",
"it",
"difficult",
"to",
"correlate",
"the",
"combinations",
"of",
"AUs",
"to",
"specific",
"emotion",
"classes.",
"Inspired",
"by",
"the",
"nodes",
"relationship",
"building",
"Graph",
"Convolutional",
"Networks",
"(GCN",
"),",
"we",
"propose",
"an",
"end-to-end",
"AU-oriented",
"graph",
"classification",
"network,",
"namely",
"MER-GCN",
",",
"which",
"uses",
"3D",
"ConvNets",
"to",
"extract",
"AU",
"features",
"and",
"applies",
"GCN",
"layers",
"to",
"discover",
"the",
"dependency",
"laying",
"between",
"AU",
"nodes",
"for",
"ME",
"categorization.",
"To",
"our",
"best",
"knowledge,",
"this",
"work",
"is",
"the",
"first",
"end-to-end",
"architecture",
"for",
"Micro-Expression",
"Recognition",
"(MER)",
"using",
"AUs",
"based",
"GCN",
".",
"The",
"experimental",
"results",
"show",
"that",
"our",
"approach",
"outperforms",
"CNN-based",
"MER",
"networks."
] |
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