tokens
list | ner_tags
list |
|---|---|
[
"Current",
"state-of-the-art",
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"hardware",
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"this,",
"we",
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"DONNA",
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"DONNA",
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"an",
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"repeats",
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"expansion",
"rates.",
"Second,",
"a",
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"architectures",
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"measurements.",
"Third,",
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"models",
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"accuracy.",
"DONNA",
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"state-of-the-art",
"architectures",
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"Classifying",
"ImageNet,",
"DONNA",
"architectures",
"are",
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"V100",
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"NAS,",
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"for",
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"extension",
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"exploration,",
"as",
"well",
"as",
"hardware-aware",
"model",
"compression."
] |
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[
"Conventional",
"Neural",
"Architecture",
"Search",
"(NAS)",
"aims",
"at",
"finding",
"a",
"single",
"architecture",
"that",
"achieves",
"the",
"best",
"performance,",
"which",
"usually",
"optimizes",
"task",
"related",
"learning",
"objectives",
"such",
"as",
"accuracy.",
"However,",
"a",
"single",
"architecture",
"may",
"not",
"be",
"representative",
"enough",
"for",
"the",
"whole",
"dataset",
"with",
"high",
"diversity",
"and",
"variety.",
"Intuitively,",
"electing",
"domain-expert",
"architectures",
"that",
"are",
"proficient",
"in",
"domain-specific",
"features",
"can",
"further",
"benefit",
"architecture",
"related",
"objectives",
"such",
"as",
"latency.",
"In",
"this",
"paper,",
"we",
"propose",
"InstaNAS---an",
"instance-aware",
"NAS",
"framework---that",
"employs",
"a",
"controller",
"trained",
"to",
"search",
"for",
"a",
"distribution\tO\nof\tO\narchitectures",
"instead",
"of",
"a",
"single",
"architecture;",
"This",
"allows",
"the",
"model",
"to",
"use",
"sophisticated",
"architectures",
"for",
"the",
"difficult",
"samples,",
"which",
"usually",
"comes",
"with",
"large",
"architecture",
"related",
"cost,",
"and",
"shallow",
"architectures",
"for",
"those",
"easy",
"samples.",
"During",
"the",
"inference",
"phase,",
"the",
"controller",
"assigns",
"each",
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"the",
"unseen",
"input",
"samples",
"with",
"a",
"domain",
"expert",
"architecture",
"that",
"can",
"achieve",
"high",
"accuracy",
"with",
"customized",
"inference",
"costs.",
"Experiments",
"within",
"a",
"search",
"space",
"inspired",
"by",
"MobileNetV2",
"show",
"InstaNAS",
"can",
"achieve",
"up",
"to",
"48.80%",
"latency",
"reduction",
"without",
"compromising",
"accuracy",
"on",
"a",
"series",
"of",
"datasets",
"against",
"MobileNetV2",
"."
] |
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[
"This",
"paper",
"presents",
"a",
"method",
"for",
"unsupervised",
"discovery",
"of",
"semantic",
"patterns",
".",
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"patterns",
"are",
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"for",
"a",
"variety",
"of",
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"understanding",
"tasks",
",",
"in",
"particular",
"for",
"locating",
"events",
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"information",
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".",
"The",
"method",
"builds",
"upon",
"previously",
"described",
"approaches",
"to",
"iterative",
"unsupervised",
"pattern",
"acquisition",
".",
"One",
"common",
"characteristic",
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"prior",
"approaches",
"is",
"that",
"the",
"output",
"of",
"the",
"algorithm",
"is",
"a",
"continuous",
"stream",
"of",
"patterns",
",",
"with",
"gradually",
"degrading",
"precision",
".",
"Our",
"method",
"differs",
"from",
"the",
"previous",
"pattern",
"acquisition",
"algorithms",
"in",
"that",
"it",
"introduces",
"competition",
"among",
"several",
"scenarios",
"simultaneously",
".",
"This",
"provides",
"natural",
"stopping",
"criteria",
"for",
"the",
"unsupervised",
"learners",
",",
"while",
"maintaining",
"good",
"precision",
"levels",
"at",
"termination",
".",
"We",
"discuss",
"the",
"results",
"of",
"experiments",
"with",
"several",
"scenarios",
",",
"and",
"examine",
"different",
"aspects",
"of",
"the",
"new",
"procedure",
"."
] |
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[
"Breaking",
"down",
"the",
"structure",
"of",
"long",
"texts",
"into",
"semantically",
"coherent",
"segments",
"makes",
"the",
"texts",
"more",
"readable",
"and",
"supports",
"downstream",
"applications",
"like",
"summarization",
"and",
"retrieval.",
"Starting",
"from",
"an",
"apparent",
"link",
"between",
"text",
"coherence",
"and",
"segmentation,",
"we",
"introduce",
"a",
"novel",
"supervised",
"model",
"for",
"text",
"segmentation",
"with",
"simple",
"but",
"explicit",
"coherence",
"modeling.",
"Our",
"model",
"--",
"a",
"neural",
"architecture",
"consisting",
"of",
"two",
"hierarchically",
"connected",
"Transformer",
"networks",
"--",
"is",
"a",
"multi-task",
"learning",
"model",
"that",
"couples",
"the",
"sentence-level",
"segmentation",
"objective",
"with",
"the",
"coherence",
"objective",
"that",
"differentiates",
"correct",
"sequences",
"of",
"sentences",
"from",
"corrupt",
"ones.",
"The",
"proposed",
"model,",
"dubbed",
"Coherence-Aware",
"Text",
"Segmentation",
"(CATS),",
"yields",
"state-of-the-art",
"segmentation",
"performance",
"on",
"a",
"collection",
"of",
"benchmark",
"datasets.",
"Furthermore,",
"by",
"coupling",
"CATS",
"with",
"cross-lingual",
"word",
"embeddings,",
"we",
"demonstrate",
"its",
"effectiveness",
"in",
"zero-shot",
"language",
"transfer:",
"it",
"can",
"successfully",
"segment",
"texts",
"in",
"languages",
"unseen",
"in",
"training."
] |
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[
"Image-to-image",
"translation",
"models",
"transfer",
"images",
"from",
"input",
"domain",
"to",
"output",
"domain",
"in",
"an",
"endeavor",
"to",
"retain",
"the",
"original",
"content",
"of",
"the",
"image.",
"Contrastive",
"Unpaired",
"Translation",
"is",
"one",
"of",
"the",
"existing",
"methods",
"for",
"solving",
"such",
"problems.",
"Significant",
"advantage",
"of",
"this",
"method,",
"compared",
"to",
"competitors,",
"is",
"the",
"ability",
"to",
"train",
"and",
"perform",
"well",
"in",
"cases",
"where",
"both",
"input",
"and",
"output",
"domains",
"are",
"only",
"a",
"single",
"image.",
"Another",
"key",
"thing",
"that",
"differentiates",
"this",
"method",
"from",
"its",
"predecessors",
"is",
"the",
"usage",
"of",
"image",
"patches",
"rather",
"than",
"the",
"whole",
"images.",
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"also",
"turns",
"out",
"that",
"sampling",
"negatives",
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"to",
"calculate",
"the",
"loss)",
"from",
"the",
"same",
"image",
"achieves",
"better",
"results",
"than",
"a",
"scenario",
"where",
"the",
"negatives",
"are",
"sampled",
"from",
"other",
"images",
"in",
"the",
"dataset.",
"This",
"type",
"of",
"approach",
"encourages",
"mapping",
"of",
"corresponding",
"patches",
"to",
"the",
"same",
"location",
"in",
"relation",
"to",
"other",
"patches",
"(negatives)",
"while",
"at",
"the",
"same",
"time",
"improves",
"the",
"output",
"image",
"quality",
"and",
"significantly",
"decreases",
"memory",
"usage",
"as",
"well",
"as",
"the",
"time",
"required",
"to",
"train",
"the",
"model",
"compared",
"to",
"CycleGAN",
"method",
"used",
"as",
"a",
"baseline.",
"Through",
"a",
"series",
"of",
"experiments",
"we",
"show",
"that",
"using",
"focal",
"loss",
"in",
"place",
"of",
"cross-entropy",
"loss",
"within",
"the",
"PatchNCE",
"loss",
"can",
"improve",
"on",
"the",
"model's",
"performance",
"and",
"even",
"surpass",
"the",
"current",
"state-of-the-art",
"model",
"for",
"image-to-image",
"translation."
] |
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[
"In",
"Computer",
"Vision,",
"Zero-Shot",
"Learning",
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"aims",
"at",
"classifying",
"unseen",
"classes",
"--",
"classes",
"for",
"which",
"no",
"matching",
"training",
"image",
"exists.",
"Most",
"of",
"ZSL",
"works",
"learn",
"a",
"cross-modal",
"mapping",
"between",
"images",
"and",
"class",
"labels",
"for",
"seen",
"classes.",
"However,",
"the",
"data",
"distribution",
"of",
"seen",
"and",
"unseen",
"classes",
"might",
"differ,",
"causing",
"a",
"domain",
"shift",
"problem.",
"Following",
"this",
"observation,",
"transductive",
"ZSL",
"(T-ZSL)",
"assumes",
"that",
"unseen",
"classes",
"and",
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"associated",
"images",
"are",
"known",
"during",
"training,",
"but",
"not",
"their",
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"As",
"current",
"T-ZSL",
"approaches",
"do",
"not",
"scale",
"efficiently",
"when",
"the",
"number",
"of",
"seen",
"classes",
"is",
"high,",
"we",
"tackle",
"this",
"problem",
"with",
"a",
"new",
"model",
"for",
"T-ZSL",
"based",
"upon",
"CycleGAN",
".",
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"model",
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"images",
"on",
"their",
"seen",
"class",
"labels",
"with",
"a",
"supervised",
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"unseen",
"class",
"labels",
"and",
"visual",
"exemplars",
"with",
"adversarial",
"and",
"cycle-consistency",
"objectives.",
"We",
"show",
"the",
"efficiency",
"of",
"our",
"Cross-Modal",
"CycleGAN",
"model",
"(CM-GAN)",
"on",
"the",
"ImageNet",
"T-ZSL",
"task",
"where",
"we",
"obtain",
"state-of-the-art",
"results.",
"We",
"further",
"validate",
"CM-GAN",
"on",
"a",
"language",
"grounding",
"task,",
"and",
"on",
"a",
"new",
"task",
"that",
"we",
"propose:",
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"sentence-to-image",
"matching",
"on",
"MS",
"COCO."
] |
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[
"Aspect-Based",
"Sentiment",
"Analysis",
"(ABSA)",
"studies",
"the",
"consumer",
"opinion",
"on",
"the",
"market",
"products.",
"It",
"involves",
"examining",
"the",
"type",
"of",
"sentiments",
"as",
"well",
"as",
"sentiment",
"targets",
"expressed",
"in",
"product",
"reviews.",
"Analyzing",
"the",
"language",
"used",
"in",
"a",
"review",
"is",
"a",
"difficult",
"task",
"that",
"requires",
"a",
"deep",
"understanding",
"of",
"the",
"language.",
"In",
"recent",
"years,",
"deep",
"language",
"models,",
"such",
"as",
"BERT",
"\\cite{devlin2019bert},",
"have",
"shown",
"great",
"progress",
"in",
"this",
"regard.",
"In",
"this",
"work,",
"we",
"propose",
"two",
"simple",
"modules",
"called",
"Parallel",
"Aggregation",
"and",
"Hierarchical",
"Aggregation",
"to",
"be",
"utilized",
"on",
"top",
"of",
"BERT",
"for",
"two",
"main",
"ABSA",
"tasks",
"namely",
"Aspect",
"Extraction",
"(AE)",
"and",
"Aspect",
"Sentiment",
"Classification",
"(ASC)",
"in",
"order",
"to",
"improve",
"the",
"model's",
"performance.",
"We",
"show",
"that",
"applying",
"the",
"proposed",
"models",
"eliminates",
"the",
"need",
"for",
"further",
"training",
"of",
"the",
"BERT",
"model.",
"The",
"source",
"code",
"is",
"available",
"on",
"the",
"Web",
"for",
"further",
"research",
"and",
"reproduction",
"of",
"the",
"results."
] |
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"Neural",
"Machine",
"Translation",
"(NMT)",
"has",
"achieved",
"remarkable",
"progress",
"with",
"the",
"quick",
"evolvement",
"of",
"model",
"structures.",
"In",
"this",
"paper,",
"we",
"propose",
"the",
"concept",
"of",
"layer-wise",
"coordination",
"for",
"NMT,",
"which",
"explicitly",
"coordinates",
"the",
"learning",
"of",
"hidden",
"representations",
"of",
"the",
"encoder",
"and",
"decoder",
"together",
"layer",
"by",
"layer,",
"gradually",
"from",
"low",
"level",
"to",
"high",
"level.",
"Specifically,",
"we",
"design",
"a",
"layer-wise",
"attention",
"and",
"mixed",
"attention",
"mechanism,",
"and",
"further",
"share",
"the",
"parameters",
"of",
"each",
"layer",
"between",
"the",
"encoder",
"and",
"decoder",
"to",
"regularize",
"and",
"coordinate",
"the",
"learning.",
"Experiments",
"show",
"that",
"combined",
"with",
"the",
"state-of-the-art",
"Transformer",
"model,",
"layer-wise",
"coordination",
"achieves",
"improvements",
"on",
"three",
"IWSLT",
"and",
"two",
"WMT",
"translation",
"tasks.",
"More",
"specifically,",
"our",
"method",
"achieves",
"34.43",
"and",
"29.01",
"BLEU",
"score",
"on",
"WMT16",
"English-Romanian",
"and",
"WMT14",
"English-German",
"tasks,",
"outperforming",
"the",
"Transformer",
"baseline."
] |
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[
"Indiscriminately",
"posting",
"offensive",
"remarks",
"on",
"social",
"media",
"may",
"promote",
"the",
"occurrence",
"of",
"negative",
"events",
"such",
"as",
"violence,",
"crime,",
"and",
"hatred.",
"This",
"paper",
"examines",
"different",
"approaches",
"and",
"models",
"for",
"solving",
"offensive",
"tweet",
"classification,",
"which",
"is",
"a",
"part",
"of",
"the",
"OffensEval",
"2020",
"competition.",
"The",
"dataset",
"is",
"Offensive",
"Language",
"Identification",
"Dataset",
"(OLID),",
"which",
"draws",
"14,200",
"annotated",
"English",
"Tweet",
"comments.",
"The",
"main",
"challenge",
"of",
"data",
"preprocessing",
"is",
"the",
"unbalanced",
"class",
"distribution,",
"abbreviation,",
"and",
"emoji.",
"To",
"overcome",
"these",
"issues,",
"methods",
"such",
"as",
"hashtag",
"segmentation,",
"abbreviation",
"replacement,",
"and",
"emoji",
"replacement",
"have",
"been",
"adopted",
"for",
"data",
"preprocessing",
"approaches.",
"The",
"main",
"task",
"can",
"be",
"divided",
"into",
"three",
"sub-tasks,",
"and",
"are",
"solved",
"by",
"Term",
"Frequency{--}Inverse",
"Document",
"Frequency(TF-IDF),",
"Bidirectional",
"Encoder",
"Representation",
"from",
"Transformer",
"(BERT",
"),",
"and",
"Multi-dropout",
"respectively.",
"Meanwhile,",
"we",
"applied",
"different",
"learning",
"rates",
"for",
"different",
"languages",
"and",
"tasks",
"based",
"on",
"BERT",
"and",
"non-BERT",
"models",
"in",
"order",
"to",
"obtain",
"better",
"results.",
"Our",
"team",
"Ferryman",
"ranked",
"the",
"18th,",
"8th,",
"and",
"21st",
"with",
"F1-score",
"of",
"0.91152",
"on",
"the",
"English",
"Sub-task",
"A,",
"Sub-task",
"B,",
"and",
"Sub-task",
"C,",
"respectively.",
"Furthermore,",
"our",
"team",
"also",
"ranked",
"in",
"the",
"top",
"20",
"on",
"the",
"Sub-task",
"A",
"of",
"other",
"languages."
] |
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[
"The",
"electroencephalographic",
"(EEG",
")",
"signals",
"provide",
"highly",
"informative",
"data",
"on",
"brain",
"activities",
"and",
"functions.",
"However,",
"their",
"heterogeneity",
"and",
"high",
"dimensionality",
"may",
"represent",
"an",
"obstacle",
"for",
"their",
"interpretation.",
"The",
"introduction",
"of",
"a",
"priori",
"knowledge",
"seems",
"the",
"best",
"option",
"to",
"mitigate",
"high",
"dimensionality",
"problems,",
"but",
"could",
"lose",
"some",
"information",
"and",
"patterns",
"present",
"in",
"the",
"data,",
"while",
"data",
"heterogeneity",
"remains",
"an",
"open",
"issue",
"that",
"often",
"makes",
"generalization",
"difficult.",
"In",
"this",
"study,",
"we",
"propose",
"a",
"genetic",
"algorithm",
"(GA",
")",
"for",
"feature",
"selection",
"that",
"can",
"be",
"used",
"with",
"a",
"supervised",
"or",
"unsupervised",
"approach.",
"Our",
"proposal",
"considers",
"three",
"different",
"fitness",
"functions",
"without",
"relying",
"on",
"expert",
"knowledge.",
"Starting",
"from",
"two",
"publicly",
"available",
"datasets",
"on",
"cognitive",
"workload",
"and",
"motor",
"movement/imagery,",
"the",
"EEG",
"signals",
"are",
"processed,",
"normalized",
"and",
"their",
"features",
"computed",
"in",
"the",
"time,",
"frequency",
"and",
"time-frequency",
"domains.",
"The",
"feature",
"vector",
"selection",
"is",
"performed",
"by",
"applying",
"our",
"GA",
"proposal",
"and",
"compared",
"with",
"two",
"benchmarking",
"techniques.",
"The",
"results",
"show",
"that",
"different",
"combinations",
"of",
"our",
"proposal",
"achieve",
"better",
"results",
"in",
"respect",
"to",
"the",
"benchmark",
"in",
"terms",
"of",
"overall",
"performance",
"and",
"feature",
"reduction.",
"Moreover,",
"the",
"proposed",
"GA",
",",
"based",
"on",
"a",
"novel",
"fitness",
"function",
"here",
"presented,",
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"the",
"benchmark",
"when",
"the",
"two",
"different",
"datasets",
"considered",
"are",
"merged",
"together,",
"showing",
"the",
"effectiveness",
"of",
"our",
"proposal",
"on",
"heterogeneous",
"data."
] |
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[
"We",
"address",
"whether",
"neural",
"models",
"for",
"Natural",
"Language",
"Inference",
"(NLI)",
"can",
"learn",
"the",
"compositional",
"interactions",
"between",
"lexical",
"entailment",
"and",
"negation,",
"using",
"four",
"methods:",
"the",
"behavioral",
"evaluation",
"methods",
"of",
"-1",
"challenge",
"test",
"sets",
"and",
"-2",
"systematic",
"generalization",
"tasks,",
"and",
"the",
"structural",
"evaluation",
"methods",
"of",
"-3",
"probes",
"and",
"-4",
"interventions.",
"To",
"facilitate",
"this",
"holistic",
"evaluation,",
"we",
"present",
"Monotonicity",
"NLI",
"(MoNLI),",
"a",
"new",
"naturalistic",
"dataset",
"focused",
"on",
"lexical",
"entailment",
"and",
"negation.",
"In",
"our",
"behavioral",
"evaluations,",
"we",
"find",
"that",
"models",
"trained",
"on",
"general-purpose",
"NLI",
"datasets",
"fail",
"systematically",
"on",
"MoNLI",
"examples",
"containing",
"negation,",
"but",
"that",
"MoNLI",
"fine-tuning",
"addresses",
"this",
"failure.",
"In",
"our",
"structural",
"evaluations,",
"we",
"look",
"for",
"evidence",
"that",
"our",
"top-performing",
"BERT",
"#NAME?",
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[
"Hierarchical",
"Text",
"Classification",
"(HTC",
"),",
"which",
"aims",
"to",
"predict",
"text",
"labels",
"organized",
"in",
"hierarchical",
"space,",
"is",
"a",
"significant",
"task",
"lacking",
"in",
"investigation",
"in",
"natural",
"language",
"processing.",
"Existing",
"methods",
"usually",
"encode",
"the",
"entire",
"hierarchical",
"structure",
"and",
"fail",
"to",
"construct",
"a",
"robust",
"label-dependent",
"model,",
"making",
"it",
"hard",
"to",
"make",
"accurate",
"predictions",
"on",
"sparse",
"lower-level",
"labels",
"and",
"achieving",
"low",
"Macro-F1.",
"In",
"this",
"paper,",
"we",
"propose",
"a",
"novel",
"PAMM-HiA-T5",
"model",
"for",
"HTC",
":",
"a",
"hierarchy-aware",
"T5",
"model",
"with",
"path-adaptive",
"mask",
"mechanism",
"that",
"not",
"only",
"builds",
"the",
"knowledge",
"of",
"upper-level",
"labels",
"into",
"low-level",
"ones",
"but",
"also",
"introduces",
"path",
"dependency",
"information",
"in",
"label",
"prediction.",
"Specifically,",
"we",
"generate",
"a",
"multi-level",
"sequential",
"label",
"structure",
"to",
"exploit",
"hierarchical",
"dependency",
"across",
"different",
"levels",
"with",
"Breadth-First",
"Search",
"(BFS)",
"and",
"T5",
"model.",
"To",
"further",
"improve",
"label",
"dependency",
"prediction",
"within",
"each",
"path,",
"we",
"then",
"propose",
"an",
"original",
"path-adaptive",
"mask",
"mechanism",
"(PAMM)",
"to",
"identify",
"the",
"label's",
"path",
"information,",
"eliminating",
"sources",
"of",
"noises",
"from",
"other",
"paths.",
"Comprehensive",
"experiments",
"on",
"three",
"benchmark",
"datasets",
"show",
"that",
"our",
"novel",
"PAMM-HiA-T5",
"model",
"greatly",
"outperforms",
"all",
"state-of-the-art",
"HTC",
"approaches",
"especially",
"in",
"Macro-F1.",
"The",
"ablation",
"studies",
"show",
"that",
"the",
"improvements",
"mainly",
"come",
"from",
"our",
"innovative",
"approach",
"instead",
"of",
"T5",
"."
] |
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[
"Large",
"labeled",
"training",
"sets",
"are",
"the",
"critical",
"building",
"blocks",
"of",
"supervisedlearning",
"methods",
"and",
"are",
"key",
"enablers",
"of",
"deep",
"learning",
"techniques.",
"For",
"someapplications,",
"creating",
"labeled",
"training",
"sets",
"is",
"the",
"most",
"time-consuming",
"andexpensive",
"part",
"of",
"applying",
"machine",
"learning.",
"We",
"therefore",
"propose",
"a",
"paradigmfor",
"the",
"programmatic",
"creation",
"of",
"training",
"sets",
"called",
"data",
"programming",
"in",
"whichusers",
"express",
"weak",
"supervision",
"strategies",
"or",
"domain",
"heuristics",
"as",
"labelingfunctions,",
"which",
"are",
"programs",
"that",
"label",
"subsets",
"of",
"the",
"data,",
"but",
"that",
"arenoisy",
"and",
"may",
"conflict.",
"We",
"show",
"that",
"by",
"explicitly",
"representing",
"this",
"trainingset",
"labeling",
"process",
"as",
"a",
"generative",
"model,",
"we",
"can",
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"generatedtraining",
"set,",
"and",
"establish",
"theoretically",
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"we",
"can",
"recover",
"the",
"parameters",
"ofthese",
"generative",
"models",
"in",
"a",
"handful",
"of",
"settings.",
"We",
"then",
"show",
"how",
"to",
"modify",
"adiscriminative",
"loss",
"function",
"to",
"make",
"it",
"noise-aware,",
"and",
"demonstrate",
"our",
"methodover",
"a",
"range",
"of",
"discriminative",
"models",
"including",
"logistic",
"regression",
"and",
"LSTM",
"s.Experimentally,",
"on",
"the",
"2014",
"TAC-KBP",
"Slot",
"Filling",
"challenge,",
"we",
"show",
"that",
"dataprogramming",
"would",
"have",
"led",
"to",
"a",
"new",
"winning",
"score,",
"and",
"also",
"show",
"that",
"applyingdata",
"programming",
"to",
"an",
"LSTM",
"model",
"leads",
"to",
"a",
"TAC-KBP",
"score",
"almost",
"6",
"F1",
"pointsover",
"a",
"state-of-the-art",
"LSTM",
"baseline",
"(and",
"into",
"second",
"place",
"in",
"thecompetition).",
"Additionally,",
"in",
"initial",
"user",
"studies",
"we",
"observed",
"that",
"dataprogramming",
"may",
"be",
"an",
"easier",
"way",
"for",
"non-experts",
"to",
"create",
"machine",
"learningmodels",
"when",
"training",
"data",
"is",
"limited",
"or",
"unavailable."
] |
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[
"Visual",
"Question",
"Answering",
"(VQA)",
"requires",
"integration",
"of",
"feature",
"maps",
"withdrastically",
"different",
"structures",
"and",
"focus",
"of",
"the",
"correct",
"regions.",
"Imagedescriptors",
"have",
"structures",
"at",
"multiple",
"spatial",
"scales,",
"while",
"lexical",
"inputsinherently",
"follow",
"a",
"temporal",
"sequence",
"and",
"naturally",
"cluster",
"into",
"semanticallydifferent",
"question",
"types.",
"A",
"lot",
"of",
"previous",
"works",
"use",
"complex",
"models",
"to",
"extractfeature",
"representations",
"but",
"neglect",
"to",
"use",
"high-level",
"information",
"summary",
"suchas",
"question",
"types",
"in",
"learning.",
"In",
"this",
"work,",
"we",
"propose",
"Question",
"Type-guidedAttention",
"(QTA).",
"It",
"utilizes",
"the",
"information",
"of",
"question",
"type",
"to",
"dynamicallybalance",
"between",
"bottom-up",
"and",
"top-down",
"visual",
"features,",
"respectively",
"extractedfrom",
"ResNet",
"and",
"Faster",
"R-CNN",
"networks.",
"We",
"experiment",
"with",
"multiple",
"VQAarchitectures",
"with",
"extensive",
"input",
"ablation",
"studies",
"over",
"the",
"TDIUC",
"dataset",
"andshow",
"that",
"QTA",
"systematically",
"improves",
"the",
"performance",
"by",
"more",
"than",
"5%",
"acrossmultiple",
"question",
"type",
"categories",
"such",
"as",
"Activity\tO\nRecognition,",
"Utility",
"and\"Counting\"",
"on",
"TDIUC",
"dataset.",
"By",
"adding",
"QTA",
"on",
"the",
"state-of-art",
"model",
"MCB,",
"weachieve",
"3%",
"improvement",
"for",
"overall",
"accuracy.",
"Finally,",
"we",
"propose",
"a",
"multi-taskextension",
"to",
"predict",
"question",
"types",
"which",
"generalizes",
"QTA",
"to",
"applications",
"thatlack",
"of",
"question",
"type,",
"with",
"minimal",
"performance",
"loss."
] |
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[
"In",
"this",
"paper,",
"we",
"introduce",
"a",
"system",
"built",
"for",
"the",
"Duolingo",
"Simultaneous",
"Translation",
"And",
"Paraphrase",
"for",
"Language",
"Education",
"(STAPLE)",
"shared",
"task",
"at",
"the",
"4th",
"Workshop",
"on",
"Neural",
"Generation",
"and",
"Translation",
"(WNGT",
"2020).",
"We",
"participated",
"in",
"the",
"English-to-Japanese",
"track",
"with",
"a",
"Transformer",
"model",
"pretrained",
"on",
"the",
"JParaCrawl",
"corpus",
"and",
"fine-tuned",
"in",
"two",
"steps",
"on",
"the",
"JESC",
"corpus",
"and",
"then",
"the",
"(smaller)",
"Duolingo",
"training",
"corpus.",
"First,",
"during",
"training,",
"we",
"find",
"it",
"is",
"essential",
"to",
"deliberately",
"expose",
"the",
"model",
"to",
"higher-quality",
"translations",
"more",
"often",
"during",
"training",
"for",
"optimal",
"translation",
"performance.",
"For",
"inference,",
"encouraging",
"a",
"small",
"amount",
"of",
"diversity",
"with",
"Diverse",
"Beam",
"Search",
"to",
"improve",
"translation",
"coverage",
"yielded",
"marginal",
"improvement",
"over",
"regular",
"Beam",
"Search.",
"Finally,",
"using",
"an",
"auxiliary",
"filtering",
"model",
"to",
"filter",
"out",
"unlikely",
"candidates",
"from",
"Beam",
"Search",
"improves",
"performance",
"further.",
"We",
"achieve",
"a",
"weighted",
"F1",
"score",
"of",
"27.56{\\%}",
"on",
"our",
"own",
"test",
"set,",
"outperforming",
"the",
"STAPLE",
"AWS",
"translations",
"baseline",
"score",
"of",
"4.31{\\%}."
] |
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[
"Dynamic",
"Multi-objective",
"Optimization",
"Problems",
"(DMOPs)",
"refer",
"to",
"optimization",
"problems",
"that",
"objective",
"functions",
"will",
"change",
"with",
"time.",
"Solving",
"DMOPs",
"implies",
"that",
"the",
"Pareto",
"Optimal",
"Set",
"(POS",
")",
"at",
"different",
"moments",
"can",
"be",
"accurately",
"found,",
"and",
"this",
"is",
"a",
"very",
"difficult",
"job",
"due",
"to",
"the",
"dynamics",
"of",
"the",
"optimization",
"problems.",
"The",
"POS",
"that",
"have",
"been",
"obtained",
"in",
"the",
"past",
"can",
"help",
"us",
"to",
"find",
"the",
"POS",
"of",
"the",
"next",
"time",
"more",
"quickly",
"and",
"accurately.",
"Therefore,",
"in",
"this",
"paper",
"we",
"present",
"a",
"Support",
"Vector",
"Machine",
"(SVM",
")",
"based",
"Dynamic",
"Multi-Objective",
"Evolutionary",
"optimization",
"Algorithm,",
"called",
"SVM",
"#NAME?",
"The",
"algorithm",
"uses",
"the",
"POS",
"that",
"has",
"been",
"obtained",
"to",
"train",
"a",
"SVM",
"and",
"then",
"take",
"the",
"trained",
"SVM",
"to",
"classify",
"the",
"solutions",
"of",
"the",
"dynamic",
"optimization",
"problem",
"at",
"the",
"next",
"moment,",
"and",
"thus",
"it",
"is",
"able",
"to",
"generate",
"an",
"initial",
"population",
"which",
"consists",
"of",
"different",
"individuals",
"recognized",
"by",
"the",
"trained",
"SVM",
".",
"The",
"initial",
"populuation",
"can",
"be",
"fed",
"into",
"any",
"population",
"based",
"optimization",
"algorithm,",
"e.g.,",
"the",
"Nondominated",
"Sorting",
"Genetic",
"Algorithm",
"II",
"(NSGA-II),",
"to",
"get",
"the",
"POS",
"at",
"that",
"moment.",
"The",
"experimental",
"results",
"show",
"the",
"validity",
"of",
"our",
"proposed",
"approach."
] |
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[
"The",
"Dynamic",
"Time",
"Warping",
"(DTW",
")",
"is",
"a",
"popular",
"similarity",
"measure",
"between",
"time",
"series.",
"The",
"DTW",
"fails",
"to",
"satisfy",
"the",
"triangle",
"inequality",
"and",
"its",
"computation",
"requires",
"quadratic",
"time.",
"Hence,",
"to",
"find",
"closest",
"neighbors",
"quickly,",
"we",
"use",
"bounding",
"techniques.",
"We",
"can",
"avoid",
"most",
"DTW",
"computations",
"with",
"an",
"inexpensive",
"lower",
"bound",
"(LB",
"Keogh).",
"We",
"compare",
"LB",
"Keogh",
"with",
"a",
"tighter",
"lower",
"bound",
"(LB",
"Improved).",
"We",
"find",
"that",
"LB",
"Improved-based",
"search",
"is",
"faster.",
"As",
"an",
"example,",
"our",
"approach",
"is",
"03-Feb",
"times",
"faster",
"over",
"random-walk",
"and",
"shape",
"time",
"series."
] |
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[
"A",
"pruning-based",
"AutoML",
"framework",
"for",
"run-time",
"reconfigurability,",
"namely",
"RT3,",
"is",
"proposed",
"in",
"this",
"work.",
"This",
"enables",
"Transformer",
"#NAME?",
"large",
"Natural",
"Language",
"Processing",
"(NLP)",
"models",
"to",
"be",
"efficiently",
"executed",
"on",
"resource-constrained",
"mobile",
"devices",
"and",
"reconfigured",
"(i.e.,",
"switching",
"models",
"for",
"dynamic",
"hardware",
"conditions)",
"at",
"run-time.",
"Such",
"reconfigurability",
"is",
"the",
"key",
"to",
"save",
"energy",
"for",
"battery-powered",
"mobile",
"devices,",
"which",
"widely",
"use",
"dynamic",
"voltage",
"and",
"frequency",
"scaling",
"(DVFS)",
"technique",
"for",
"hardware",
"reconfiguration",
"to",
"prolong",
"battery",
"life.",
"In",
"this",
"work,",
"we",
"creatively",
"explore",
"a",
"hybrid",
"block-structured",
"pruning",
"(BP)",
"and",
"pattern",
"pruning",
"(PP)",
"for",
"Transformer",
"#NAME?",
"models",
"and",
"first",
"attempt",
"to",
"combine",
"hardware",
"and",
"software",
"reconfiguration",
"to",
"maximally",
"save",
"energy",
"for",
"battery-powered",
"mobile",
"devices.",
"Specifically,",
"RT3",
"integrates",
"two-level",
"optimizations:",
"First,",
"it",
"utilizes",
"an",
"efficient",
"BP",
"as",
"the",
"first-step",
"compression",
"for",
"resource-constrained",
"mobile",
"devices;",
"then,",
"RT3",
"heuristically",
"generates",
"a",
"shrunken",
"search",
"space",
"based",
"on",
"the",
"first",
"level",
"optimization",
"and",
"searches",
"multiple",
"pattern",
"sets",
"with",
"diverse",
"sparsity",
"for",
"PP",
"via",
"reinforcement",
"learning",
"to",
"support",
"lightweight",
"software",
"reconfiguration,",
"which",
"corresponds",
"to",
"available",
"frequency",
"levels",
"of",
"DVFS",
"(i.e.,",
"hardware",
"reconfiguration).",
"At",
"run-time,",
"RT3",
"can",
"switch",
"the",
"lightweight",
"pattern",
"sets",
"within",
"45ms",
"to",
"guarantee",
"the",
"required",
"real-time",
"constraint",
"at",
"different",
"frequency",
"levels.",
"Results",
"further",
"show",
"that",
"RT3",
"can",
"prolong",
"battery",
"life",
"over",
"4x",
"improvement",
"with",
"less",
"than",
"1%",
"accuracy",
"loss",
"for",
"Transformer",
"and",
"1.50%",
"score",
"decrease",
"for",
"DistilBERT."
] |
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[
"This",
"paper",
"focuses",
"on",
"distributed",
"learning-based",
"control",
"of",
"decentralized",
"multi-agent",
"systems",
"where",
"the",
"agents'",
"dynamics",
"are",
"modeled",
"by",
"Gaussian",
"Processes",
"(GPs).",
"Two",
"fundamental",
"problems",
"are",
"considered:",
"the",
"optimal",
"design",
"of",
"experiment",
"for",
"concurrent",
"learning",
"of",
"the",
"agents'",
"GP",
"models,",
"and",
"the",
"distributed",
"coordination",
"given",
"the",
"learned",
"models.",
"Using",
"a",
"Distributed",
"Model",
"Predictive",
"Control",
"(DMPC)",
"approach,",
"the",
"two",
"problems",
"are",
"formulated",
"as",
"distributed",
"optimization",
"problems,",
"where",
"each",
"agent's",
"sub-problem",
"includes",
"both",
"local",
"and",
"shared",
"objectives",
"and",
"constraints.",
"To",
"solve",
"the",
"resulting",
"complex",
"and",
"non-convex",
"DMPC",
"problems",
"efficiently,",
"we",
"develop",
"an",
"algorithm",
"called",
"Alternating",
"Direction",
"Method",
"of",
"Multipliers",
"with",
"Convexification",
"(ADMM",
"-C)",
"that",
"combines",
"a",
"distributed",
"ADMM",
"algorithm",
"and",
"a",
"Sequential",
"Convexification",
"method.",
"The",
"computational",
"efficiency",
"of",
"our",
"proposed",
"method",
"comes",
"from",
"the",
"facts",
"that",
"the",
"computation",
"for",
"solving",
"the",
"DMPC",
"problem",
"is",
"distributed",
"to",
"all",
"agents",
"and",
"that",
"efficient",
"convex",
"optimization",
"solvers",
"are",
"used",
"at",
"the",
"agents",
"for",
"solving",
"the",
"convexified",
"sub-problems.",
"We",
"also",
"prove",
"that,",
"under",
"some",
"technical",
"assumptions,",
"the",
"ADMM",
"-C",
"algorithm",
"converges",
"to",
"a",
"stationary",
"point",
"of",
"the",
"penalized",
"optimization",
"problem.",
"The",
"effectiveness",
"of",
"our",
"approach",
"is",
"demonstrated",
"in",
"numerical",
"simulations",
"of",
"a",
"multi-vehicle",
"formation",
"control",
"example."
] |
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[
"Deep",
"Neural",
"Networks",
"(DNN)",
"represent",
"the",
"state",
"of",
"the",
"art",
"in",
"many",
"tasks.",
"However,",
"due",
"to",
"their",
"overparameterization,",
"their",
"generalization",
"capabilities",
"are",
"in",
"doubt",
"and",
"still",
"a",
"field",
"under",
"study.",
"Consequently,",
"DNN",
"can",
"overfit",
"and",
"assign",
"overconfident",
"predictions",
"--",
"effects",
"that",
"have",
"been",
"shown",
"to",
"affect",
"the",
"calibration",
"of",
"the",
"confidences",
"assigned",
"to",
"unseen",
"data.",
"Data",
"Augmentation",
"(DA)",
"strategies",
"have",
"been",
"proposed",
"to",
"regularize",
"these",
"models,",
"being",
"Mixup",
"one",
"of",
"the",
"most",
"popular",
"due",
"to",
"its",
"ability",
"to",
"improve",
"the",
"accuracy,",
"the",
"uncertainty",
"quantification",
"and",
"the",
"calibration",
"of",
"DNN.",
"In",
"this",
"work",
"however",
"we",
"argue",
"and",
"provide",
"empirical",
"evidence",
"that,",
"due",
"to",
"its",
"fundamentals,",
"Mixup",
"does",
"not",
"necessarily",
"improve",
"calibration.",
"Based",
"on",
"our",
"observations",
"we",
"propose",
"a",
"new",
"loss",
"function",
"that",
"improves",
"the",
"calibration,",
"and",
"also",
"sometimes",
"the",
"accuracy,",
"of",
"DNN",
"trained",
"with",
"this",
"DA",
"technique.",
"Our",
"loss",
"is",
"inspired",
"by",
"Bayes",
"decision",
"theory",
"and",
"introduces",
"a",
"new",
"training",
"framework",
"for",
"designing",
"losses",
"for",
"probabilistic",
"modelling.",
"We",
"provide",
"state-of-the-art",
"accuracy",
"with",
"consistent",
"improvements",
"in",
"calibration",
"performance.",
"Appendix",
"and",
"code",
"are",
"provided",
"here:",
"https://github.com/jmaronas/calibration_Mixup",
"DNN_ARCLoss.pytorch.git"
] |
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[
"We",
"present",
"a",
"method",
"of",
"inferring",
"aspects",
"of",
"a",
"person",
"'s",
"context",
"by",
"capturing",
"conversation",
"topics",
"and",
"using",
"prior",
"knowledge",
"of",
"human",
"behavior",
".",
"This",
"paper",
"claims",
"that",
"topic-spotting",
"performance",
"can",
"be",
"improved",
"by",
"using",
"a",
"large",
"database",
"of",
"common",
"sense",
"knowledge",
".",
"We",
"describe",
"two",
"systems",
"we",
"built",
"to",
"infer",
"context",
"from",
"noisy",
"transcriptions",
"of",
"spoken",
"conversations",
"using",
"common",
"sense",
",",
"and",
"detail",
"some",
"preliminary",
"results",
".",
"The",
"GISTER",
"system",
"uses",
"OMCSNet",
",",
"a",
"commonsense",
"semantic",
"network",
",",
"to",
"infer",
"the",
"most",
"likely",
"topics",
"under",
"discussion",
"in",
"a",
"conversation",
"stream",
".",
"The",
"OVERHEAR",
"system",
"is",
"built",
"on",
"top",
"of",
"GISTER",
",",
"and",
"distinguishes",
"between",
"aspects",
"of",
"the",
"conversation",
"that",
"refer",
"to",
"past",
",",
"present",
",",
"and",
"future",
"events",
"by",
"using",
"LifeNet",
",",
"a",
"probabilistic",
"graphical",
"model",
"of",
"human",
"behavior",
",",
"to",
"help",
"infer",
"the",
"events",
"that",
"occurred",
"in",
"each",
"of",
"those",
"three",
"time",
"periods",
".",
"We",
"conclude",
"by",
"discussing",
"some",
"of",
"the",
"future",
"directions",
"we",
"may",
"take",
"this",
"work",
"."
] |
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[
"Intent",
"and",
"Slot",
"Identification",
"are",
"two",
"important",
"tasks",
"in",
"Spoken",
"Language",
"Understanding",
"(SLU).",
"For",
"a",
"natural",
"language",
"utterance,",
"there",
"is",
"a",
"high",
"correlation",
"between",
"these",
"two",
"tasks.",
"A",
"lot",
"of",
"work",
"has",
"been",
"done",
"on",
"each",
"of",
"these",
"using",
"Recurrent-Neural-Networks",
"(RNN),",
"Convolution",
"Neural",
"Networks",
"(CNN)",
"and",
"Attention",
"based",
"models.",
"Most",
"of",
"the",
"past",
"work",
"used",
"two",
"separate",
"models",
"for",
"intent",
"and",
"slot",
"prediction.",
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"them",
"also",
"used",
"sequence-to-sequence",
"type",
"models",
"where",
"slots",
"are",
"predicted",
"after",
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"the",
"utterance-level",
"intent.",
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"this",
"work,",
"we",
"propose",
"a",
"parallel",
"Intent",
"and",
"Slot",
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"technique",
"where",
"separate",
"Bidirectional",
"Gated",
"Recurrent",
"Units",
"(GRU)",
"are",
"used",
"for",
"each",
"task.",
"We",
"posit",
"the",
"usage",
"of",
"MLB",
"(Multimodal",
"Low-rank",
"Bilinear",
"Attention",
"Network)",
"fusion",
"for",
"improvement",
"in",
"performance",
"of",
"intent",
"and",
"slot",
"learning.",
"To",
"the",
"best",
"of",
"our",
"knowledge,",
"this",
"is",
"the",
"first",
"attempt",
"of",
"using",
"such",
"a",
"technique",
"on",
"text",
"based",
"problems.",
"Also,",
"our",
"proposed",
"methods",
"outperform",
"the",
"existing",
"state-of-the-art",
"results",
"for",
"both",
"intent",
"and",
"slot",
"prediction",
"on",
"two",
"benchmark",
"datasets"
] |
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[
"The",
"COVID-19",
"pandemic",
"has",
"become",
"one",
"of",
"the",
"biggest",
"threats",
"to",
"the",
"global",
"healthcare",
"system,",
"creating",
"an",
"unprecedented",
"condition",
"worldwide.",
"The",
"necessity",
"of",
"rapid",
"diagnosis",
"calls",
"for",
"alternative",
"methods",
"to",
"predict",
"the",
"condition",
"of",
"the",
"patient,",
"for",
"which",
"disease",
"severity",
"estimation",
"on",
"the",
"basis",
"of",
"Lung",
"Ultrasound",
"(LUS)",
"can",
"be",
"a",
"safe,",
"radiation-free,",
"flexible,",
"and",
"favorable",
"option.",
"In",
"this",
"paper,",
"a",
"frame-based",
"4-score",
"disease",
"severity",
"prediction",
"architecture",
"is",
"proposed",
"with",
"the",
"integration",
"of",
"deep",
"convolutional",
"and",
"recurrent",
"neural",
"networks",
"to",
"consider",
"both",
"spatial",
"and",
"temporal",
"features",
"of",
"the",
"LUS",
"frames.",
"The",
"proposed",
"convolutional",
"neural",
"network",
"(CNN)",
"architecture",
"implements",
"an",
"autoencoder",
"network",
"and",
"separable",
"convolutional",
"branches",
"fused",
"with",
"a",
"modified",
"DenseNet",
"-201",
"network",
"to",
"build",
"a",
"vigorous,",
"noise-free",
"classification",
"model.",
"A",
"five-fold",
"cross-validation",
"scheme",
"is",
"performed",
"to",
"affirm",
"the",
"efficacy",
"of",
"the",
"proposed",
"network.",
"In-depth",
"result",
"analysis",
"shows",
"a",
"promising",
"improvement",
"in",
"the",
"classification",
"performance",
"by",
"introducing",
"the",
"Long",
"Short-Term",
"Memory",
"(LSTM)",
"layers",
"after",
"the",
"proposed",
"CNN",
"architecture",
"by",
"an",
"average",
"of",
"7-12%,",
"which",
"is",
"approximately",
"17%",
"more",
"than",
"the",
"traditional",
"DenseNet",
"architecture",
"alone.",
"From",
"an",
"extensive",
"analysis,",
"it",
"is",
"found",
"that",
"the",
"proposed",
"end-to-end",
"scheme",
"is",
"very",
"effective",
"in",
"detecting",
"COVID-19",
"severity",
"scores",
"from",
"LUS",
"images."
] |
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"domain",
"adaptation",
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"predictions",
"for",
"unlabeled",
"data",
"on",
"a",
"target",
"domain,",
"given",
"labeled",
"data",
"on",
"a",
"source",
"domain",
"whose",
"distribution",
"shifts",
"from",
"the",
"target",
"one.",
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"UDA",
"methods",
"learn",
"aligned",
"features",
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"the",
"two",
"domains,",
"such",
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"a",
"classifier",
"trained",
"on",
"the",
"source",
"features",
"can",
"be",
"readily",
"applied",
"to",
"the",
"target",
"ones.",
"However,",
"such",
"a",
"transferring",
"strategy",
"has",
"a",
"potential",
"risk",
"of",
"damaging",
"the",
"intrinsic",
"discrimination",
"of",
"target",
"data.",
"To",
"alleviate",
"this",
"risk,",
"we",
"are",
"motivated",
"by",
"the",
"assumption",
"of",
"structural",
"domain",
"similarity,",
"and",
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"directly",
"uncover",
"the",
"intrinsic",
"target",
"discrimination",
"via",
"discriminative",
"clustering",
"of",
"target",
"data.",
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"constrain",
"the",
"clustering",
"solutions",
"using",
"structural",
"source",
"regularization",
"that",
"hinges",
"on",
"our",
"assumed",
"structural",
"domain",
"similarity.",
"Technically,",
"we",
"use",
"a",
"flexible",
"framework",
"of",
"deep",
"network",
"based",
"discriminative",
"clustering",
"that",
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"the",
"KL",
"divergence",
"between",
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"label",
"distribution",
"of",
"the",
"network",
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"auxiliary",
"one;",
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"auxiliary",
"distribution",
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"by",
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"data",
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"structural",
"source",
"regularization",
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"simple",
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"of",
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"network",
"training.",
"We",
"term",
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"method",
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"Regularized",
"Deep",
"Clustering",
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"),",
"where",
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"network",
"features,",
"and",
"enhance",
"structural",
"regularization",
"with",
"soft",
"selection",
"of",
"less",
"divergent",
"source",
"examples.",
"Careful",
"ablation",
"studies",
"show",
"the",
"efficacy",
"of",
"our",
"proposed",
"SRDC",
".",
"Notably,",
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"no",
"explicit",
"domain",
"alignment,",
"SRDC",
"outperforms",
"all",
"existing",
"methods",
"on",
"three",
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"benchmarks."
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[
"Automated",
"Facial",
"Expression",
"Recognition",
"(FER)",
"has",
"been",
"a",
"challenging",
"task",
"fordecades.",
"Many",
"of",
"the",
"existing",
"works",
"use",
"hand-crafted",
"features",
"such",
"as",
"LBP,",
"HOG,LPQ,",
"and",
"Histogram",
"of",
"Optical",
"Flow",
"(HOF)",
"combined",
"with",
"classifiers",
"such",
"asSupport",
"Vector",
"Machines",
"for",
"expression",
"recognition.",
"These",
"methods",
"often",
"requirerigorous",
"hyperparameter",
"tuning",
"to",
"achieve",
"good",
"results.",
"Recently",
"Deep",
"NeuralNetworks",
"(DNN)",
"have",
"shown",
"to",
"outperform",
"traditional",
"methods",
"in",
"visual",
"objectrecognition.",
"In",
"this",
"paper,",
"we",
"propose",
"a",
"two-part",
"network",
"consisting",
"of",
"aDNN-based",
"architecture",
"followed",
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"a",
"Conditional",
"Random",
"Field",
"(CRF",
")",
"module",
"forfacial",
"expression",
"recognition",
"in",
"videos.",
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"first",
"part",
"captures",
"the",
"spatialrelation",
"within",
"facial",
"images",
"using",
"convolutional",
"layers",
"followed",
"by",
"threeInception-ResNet",
"modules",
"and",
"two",
"fully-connected",
"layers.",
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"capture",
"thetemporal",
"relation",
"between",
"the",
"image",
"frames,",
"we",
"use",
"linear",
"chain",
"CRF",
"in",
"thesecond",
"part",
"of",
"our",
"network.",
"We",
"evaluate",
"our",
"proposed",
"network",
"on",
"three",
"publiclyavailable",
"databases,",
"viz.",
"CK+,",
"MMI,",
"and",
"FERA.",
"Experiments",
"are",
"performed",
"insubject-independent",
"and",
"cross-database",
"manners.",
"Our",
"experimental",
"results",
"showthat",
"cascading",
"the",
"deep",
"network",
"architecture",
"with",
"the",
"CRF",
"module",
"considerablyincreases",
"the",
"recognition",
"of",
"facial",
"expressions",
"in",
"videos",
"and",
"in",
"particular",
"itoutperforms",
"the",
"state-of-the-art",
"methods",
"in",
"the",
"cross-database",
"experiments",
"andyields",
"comparable",
"results",
"in",
"the",
"subject-independent",
"experiments."
] |
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6,
6,
6,
6,
6,
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[
"Convolutional",
"Neural",
"Networks",
"(CNNs)",
"have",
"had",
"great",
"success",
"in",
"many",
"machine",
"vision",
"as",
"well",
"as",
"machine",
"audition",
"tasks.",
"Many",
"image",
"recognition",
"network",
"architectures",
"have",
"consequently",
"been",
"adapted",
"for",
"audio",
"processing",
"tasks.",
"However,",
"despite",
"some",
"successes,",
"the",
"performance",
"of",
"many",
"of",
"these",
"did",
"not",
"translate",
"from",
"the",
"image",
"to",
"the",
"audio",
"domain.",
"For",
"example,",
"very",
"deep",
"architectures",
"such",
"as",
"ResNet",
"and",
"DenseNet,",
"which",
"significantly",
"outperform",
"VGG",
"in",
"image",
"recognition,",
"do",
"not",
"perform",
"better",
"in",
"audio",
"processing",
"tasks",
"such",
"as",
"Acoustic",
"Scene",
"Classification",
"(ASC).",
"In",
"this",
"paper,",
"we",
"investigate",
"the",
"reasons",
"why",
"such",
"powerful",
"architectures",
"perform",
"worse",
"in",
"ASC",
"compared",
"to",
"simpler",
"models",
"(e.g.,",
"VGG",
").",
"To",
"this",
"end,",
"we",
"analyse",
"the",
"receptive",
"field",
"(RF)",
"of",
"these",
"CNNs",
"and",
"demonstrate",
"the",
"importance",
"of",
"the",
"RF",
"to",
"the",
"generalization",
"capability",
"of",
"the",
"models.",
"Using",
"our",
"receptive",
"field",
"analysis,",
"we",
"adapt",
"both",
"ResNet",
"and",
"DenseNet,",
"achieving",
"state-of-the-art",
"performance",
"and",
"eventually",
"outperforming",
"the",
"VGG",
"#NAME?",
"models.",
"We",
"introduce",
"systematic",
"ways",
"of",
"adapting",
"the",
"RF",
"in",
"CNNs,",
"and",
"present",
"results",
"on",
"three",
"data",
"sets",
"that",
"show",
"how",
"changing",
"the",
"RF",
"over",
"the",
"time",
"and",
"frequency",
"dimensions",
"affects",
"a",
"model's",
"performance.",
"Our",
"experimental",
"results",
"show",
"that",
"very",
"small",
"or",
"very",
"large",
"RFs",
"can",
"cause",
"performance",
"degradation,",
"but",
"deep",
"models",
"can",
"be",
"made",
"to",
"generalize",
"well",
"by",
"carefully",
"choosing",
"an",
"appropriate",
"RF",
"size",
"within",
"a",
"certain",
"range."
] |
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[
"Recently,",
"large",
"pre-trained",
"language",
"models,",
"such",
"as",
"BERT",
",",
"have",
"reached",
"state-of-the-art",
"performance",
"in",
"many",
"natural",
"language",
"processing",
"tasks,",
"but",
"for",
"many",
"languages,",
"including",
"Estonian,",
"BERT",
"models",
"are",
"not",
"yet",
"available.",
"However,",
"there",
"exist",
"several",
"multilingual",
"BERT",
"models",
"that",
"can",
"handle",
"multiple",
"languages",
"simultaneously",
"and",
"that",
"have",
"been",
"trained",
"also",
"on",
"Estonian",
"data.",
"In",
"this",
"paper,",
"we",
"evaluate",
"four",
"multilingual",
"models",
"--",
"multilingual",
"BERT",
",",
"multilingual",
"distilled",
"BERT",
",",
"XLM",
"and",
"XLM",
"#NAME?",
"a",
"--",
"on",
"several",
"NLP",
"tasks",
"including",
"POS",
"and",
"morphological",
"tagging,",
"NER",
"and",
"text",
"classification.",
"Our",
"aim",
"is",
"to",
"establish",
"a",
"comparison",
"between",
"these",
"multilingual",
"BERT",
"models",
"and",
"the",
"existing",
"baseline",
"neural",
"models",
"for",
"these",
"tasks.",
"Our",
"results",
"show",
"that",
"multilingual",
"BERT",
"models",
"can",
"generalise",
"well",
"on",
"different",
"Estonian",
"NLP",
"tasks",
"outperforming",
"all",
"baselines",
"models",
"for",
"POS",
"and",
"morphological",
"tagging",
"and",
"text",
"classification,",
"and",
"reaching",
"the",
"comparable",
"level",
"with",
"the",
"best",
"baseline",
"for",
"NER",
",",
"with",
"XLM",
"#NAME?",
"a",
"achieving",
"the",
"highest",
"results",
"compared",
"with",
"other",
"multilingual",
"models."
] |
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[
"Human",
"action",
"recognition",
"from",
"skeleton",
"data,",
"fueled",
"by",
"the",
"Graph",
"Convolutional",
"Network",
"(GCN",
"),",
"has",
"attracted",
"lots",
"of",
"attention,",
"due",
"to",
"its",
"powerful",
"capability",
"of",
"modeling",
"non-Euclidean",
"structure",
"data.",
"However,",
"many",
"existing",
"GCN",
"methods",
"provide",
"a",
"pre-defined",
"graph",
"and",
"fix",
"it",
"through",
"the",
"entire",
"network,",
"which",
"can",
"loss",
"implicit",
"joint",
"correlations.",
"Besides,",
"the",
"mainstream",
"spectral",
"GCN",
"is",
"approximated",
"by",
"one-order",
"hop,",
"thus",
"higher-order",
"connections",
"are",
"not",
"well",
"involved.",
"Therefore,",
"huge",
"efforts",
"are",
"required",
"to",
"explore",
"a",
"better",
"GCN",
"architecture.",
"To",
"address",
"these",
"problems,",
"we",
"turn",
"to",
"Neural",
"Architecture",
"Search",
"(NAS)",
"and",
"propose",
"the",
"first",
"automatically",
"designed",
"GCN",
"for",
"skeleton-based",
"action",
"recognition.",
"Specifically,",
"we",
"enrich",
"the",
"search",
"space",
"by",
"providing",
"multiple",
"dynamic",
"graph",
"modules",
"after",
"fully",
"exploring",
"the",
"spatial-temporal",
"correlations",
"between",
"nodes.",
"Besides,",
"we",
"introduce",
"multiple-hop",
"modules",
"and",
"expect",
"to",
"break",
"the",
"limitation",
"of",
"representational",
"capacity",
"caused",
"by",
"one-order",
"approximation.",
"Moreover,",
"a",
"sampling-",
"and",
"memory-efficient",
"evolution",
"strategy",
"is",
"proposed",
"to",
"search",
"an",
"optimal",
"architecture",
"for",
"this",
"task.",
"The",
"resulted",
"architecture",
"proves",
"the",
"effectiveness",
"of",
"the",
"higher-order",
"approximation",
"and",
"the",
"dynamic",
"graph",
"modeling",
"mechanism",
"with",
"temporal",
"interactions,",
"which",
"is",
"barely",
"discussed",
"before.",
"To",
"evaluate",
"the",
"performance",
"of",
"the",
"searched",
"model,",
"we",
"conduct",
"extensive",
"experiments",
"on",
"two",
"very",
"large",
"scaled",
"datasets",
"and",
"the",
"results",
"show",
"that",
"our",
"model",
"gets",
"the",
"state-of-the-art",
"results."
] |
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[
"The",
"surge",
"of",
"pre-trained",
"language",
"models",
"has",
"begun",
"a",
"new",
"era",
"in",
"the",
"field",
"of",
"Natural",
"Language",
"Processing",
"(NLP)",
"by",
"allowing",
"us",
"to",
"build",
"powerful",
"language",
"models.",
"Among",
"these",
"models,",
"Transformer-based",
"models",
"such",
"as",
"BERT",
"have",
"become",
"increasingly",
"popular",
"due",
"to",
"their",
"state-of-the-art",
"performance.",
"However,",
"these",
"models",
"are",
"usually",
"focused",
"on",
"English,",
"leaving",
"other",
"languages",
"to",
"multilingual",
"models",
"with",
"limited",
"resources.",
"This",
"paper",
"proposes",
"a",
"monolingual",
"BERT",
"for",
"the",
"Persian",
"language",
"(ParsBERT",
"),",
"which",
"shows",
"its",
"state-of-the-art",
"performance",
"compared",
"to",
"other",
"architectures",
"and",
"multilingual",
"models.",
"Also,",
"since",
"the",
"amount",
"of",
"data",
"available",
"for",
"NLP",
"tasks",
"in",
"Persian",
"is",
"very",
"restricted,",
"a",
"massive",
"dataset",
"for",
"different",
"NLP",
"tasks",
"as",
"well",
"as",
"pre-training",
"the",
"model",
"is",
"composed.",
"ParsBERT",
"obtains",
"higher",
"scores",
"in",
"all",
"datasets,",
"including",
"existing",
"ones",
"as",
"well",
"as",
"composed",
"ones",
"and",
"improves",
"the",
"state-of-the-art",
"performance",
"by",
"outperforming",
"both",
"multilingual",
"BERT",
"and",
"other",
"prior",
"works",
"in",
"Sentiment",
"Analysis,",
"Text",
"Classification",
"and",
"Named",
"Entity",
"Recognition",
"tasks."
] |
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[
"Can",
"we",
"complete",
"pre-training",
"of",
"Vision",
"Transformers",
"(ViT)",
"without",
"natural",
"images",
"and",
"human-annotated",
"labels?",
"Although",
"a",
"pre-trained",
"ViT",
"seems",
"to",
"heavily",
"rely",
"on",
"a",
"large-scale",
"dataset",
"and",
"human-annotated",
"labels,",
"recent",
"large-scale",
"datasets",
"contain",
"several",
"problems",
"in",
"terms",
"of",
"privacy",
"violations,",
"inadequate",
"fairness",
"protection,",
"and",
"labor-intensive",
"annotation.",
"In",
"the",
"present",
"paper,",
"we",
"pre-train",
"ViT",
"without",
"any",
"image",
"collections",
"and",
"annotation",
"labor.",
"We",
"experimentally",
"verify",
"that",
"our",
"proposed",
"framework",
"partially",
"outperforms",
"sophisticated",
"Self-Supervised",
"Learning",
"(SSL)",
"methods",
"like",
"SimCLRv2",
"and",
"MoCov2",
"without",
"using",
"any",
"natural",
"images",
"in",
"the",
"pre-training",
"phase.",
"Moreover,",
"although",
"the",
"ViT",
"pre-trained",
"without",
"natural",
"images",
"produces",
"some",
"different",
"visualizations",
"from",
"ImageNet",
"pre-trained",
"ViT,",
"it",
"can",
"interpret",
"natural",
"image",
"datasets",
"to",
"a",
"large",
"extent.",
"For",
"example,",
"the",
"performance",
"rates",
"on",
"the",
"CIFAR-10",
"dataset",
"are",
"as",
"follows:",
"our",
"proposal",
"97.6",
"vs.",
"SimCLRv2",
"97.4",
"vs.",
"ImageNet",
"98.0."
] |
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[
"Biological",
"agents",
"are",
"known",
"to",
"learn",
"many",
"different",
"tasks",
"over",
"the",
"course",
"of",
"their",
"lives,",
"and",
"to",
"be",
"able",
"to",
"revisit",
"previous",
"tasks",
"and",
"behaviors",
"with",
"little",
"to",
"no",
"loss",
"in",
"performance.",
"In",
"contrast,",
"artificial",
"agents",
"are",
"prone",
"to",
"'catastrophic",
"forgetting'",
"whereby",
"performance",
"on",
"previous",
"tasks",
"deteriorates",
"rapidly",
"as",
"new",
"ones",
"are",
"acquired.",
"This",
"shortcoming",
"has",
"recently",
"been",
"addressed",
"using",
"methods",
"that",
"encourage",
"parameters",
"to",
"stay",
"close",
"to",
"those",
"used",
"for",
"previous",
"tasks.",
"This",
"can",
"be",
"done",
"by",
"(i)",
"using",
"specific",
"parameter",
"regularizers",
"that",
"map",
"out",
"suitable",
"destinations",
"in",
"parameter",
"space,",
"or",
"(ii)",
"guiding",
"the",
"optimization",
"journey",
"by",
"projecting",
"gradients",
"into",
"subspaces",
"that",
"do",
"not",
"interfere",
"with",
"previous",
"tasks.",
"However,",
"parameter",
"regularization",
"has",
"been",
"shown",
"to",
"be",
"relatively",
"ineffective",
"in",
"recurrent",
"neural",
"networks",
"(RNNs),",
"a",
"setting",
"relevant",
"to",
"the",
"study",
"of",
"neural",
"dynamics",
"supporting",
"biological",
"continual",
"learning.",
"Similarly,",
"projection",
"based",
"methods",
"can",
"reach",
"capacity",
"and",
"fail",
"to",
"learn",
"any",
"further",
"as",
"the",
"number",
"of",
"tasks",
"increases.",
"To",
"address",
"these",
"limitations,",
"we",
"propose",
"Natural",
"Continual",
"Learning",
"(NCL",
"),",
"a",
"new",
"method",
"that",
"unifies",
"weight",
"regularization",
"and",
"projected",
"gradient",
"descent.",
"NCL",
"uses",
"Bayesian",
"weight",
"regularization",
"to",
"encourage",
"good",
"performance",
"on",
"all",
"tasks",
"at",
"convergence",
"and",
"combines",
"this",
"with",
"gradient",
"projections",
"designed",
"to",
"prevent",
"catastrophic",
"forgetting",
"during",
"optimization.",
"NCL",
"formalizes",
"gradient",
"projection",
"as",
"a",
"trust",
"region",
"algorithm",
"based",
"on",
"the",
"Fisher",
"information",
"metric,",
"and",
"achieves",
"scalability",
"via",
"a",
"novel",
"Kronecker-factored",
"approximation",
"strategy.",
"Our",
"method",
"outperforms",
"both",
"standard",
"weight",
"regularization",
"techniques",
"and",
"projection",
"based",
"approaches",
"when",
"applied",
"to",
"continual",
"learning",
"problems",
"in",
"RNNs.",
"The",
"trained",
"networks",
"evolve",
"task-specific",
"dynamics",
"that",
"are",
"strongly",
"preserved",
"as",
"new",
"tasks",
"are",
"learned,",
"similar",
"to",
"experimental",
"findings",
"in",
"biological",
"circuits."
] |
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[
"Subjectivity",
"in",
"natural",
"language",
"refers",
"to",
"aspects",
"of",
"language",
"used",
"to",
"express",
"opinions",
",",
"evaluations",
",",
"and",
"speculations",
".",
"There",
"are",
"numerous",
"natural",
"language",
"processing",
"applications",
"for",
"which",
"subjectivity",
"analysis",
"is",
"relevant",
",",
"including",
"information",
"extraction",
"and",
"text",
"categorization",
".",
"The",
"goal",
"of",
"this",
"work",
"is",
"learning",
"subjective",
"language",
"from",
"corpora",
".",
"Clues",
"of",
"subjectivity",
"are",
"generated",
"and",
"tested",
",",
"including",
"low-frequency",
"words",
",",
"collocations",
",",
"and",
"adjectives",
"and",
"verbs",
"identified",
"using",
"distributional",
"similarity",
".",
"The",
"features",
"are",
"also",
"examined",
"working",
"together",
"in",
"concert",
".",
"The",
"features",
",",
"generated",
"from",
"different",
"data",
"sets",
"using",
"different",
"procedures",
",",
"exhibit",
"consistency",
"in",
"performance",
"in",
"that",
"they",
"all",
"do",
"better",
"and",
"worse",
"on",
"the",
"same",
"data",
"sets",
".",
"In",
"addition",
",",
"this",
"article",
"shows",
"that",
"the",
"density",
"of",
"subjectivity",
"clues",
"in",
"the",
"surrounding",
"context",
"strongly",
"affects",
"how",
"likely",
"it",
"is",
"that",
"a",
"word",
"is",
"subjective",
",",
"and",
"it",
"provides",
"the",
"results",
"of",
"an",
"annotation",
"study",
"assessing",
"the",
"subjectivity",
"of",
"sentences",
"with",
"high-density",
"features",
".",
"Finally",
",",
"the",
"clues",
"are",
"used",
"to",
"perform",
"opinion",
"piece",
"recognition",
"-LRB-",
"a",
"type",
"of",
"text",
"categorization",
"and",
"genre",
"detection",
"-RRB-",
"to",
"demonstrate",
"the",
"utility",
"of",
"the",
"knowledge",
"acquired",
"in",
"this",
"article",
"."
] |
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[
"Video",
"transformers",
"have",
"recently",
"emerged",
"as",
"a",
"competitive",
"alternative",
"to",
"3D",
"CNNs",
"for",
"video",
"understanding.",
"However,",
"due",
"to",
"their",
"large",
"number",
"of",
"parameters",
"and",
"reduced",
"inductive",
"biases,",
"these",
"models",
"require",
"supervised",
"pretraining",
"on",
"large-scale",
"image",
"datasets",
"to",
"achieve",
"top",
"performance.",
"In",
"this",
"paper,",
"we",
"empirically",
"demonstrate",
"that",
"self-supervised",
"pretraining",
"of",
"video",
"transformers",
"on",
"video-only",
"datasets",
"can",
"lead",
"to",
"action",
"recognition",
"results",
"that",
"are",
"on",
"par",
"or",
"better",
"than",
"those",
"obtained",
"with",
"supervised",
"pretraining",
"on",
"large-scale",
"image",
"datasets,",
"even",
"massive",
"ones",
"such",
"as",
"ImageNet-21K.",
"Since",
"transformer-based",
"models",
"are",
"effective",
"at",
"capturing",
"dependencies",
"over",
"extended",
"temporal",
"spans,",
"we",
"propose",
"a",
"simple",
"learning",
"procedure",
"that",
"forces",
"the",
"model",
"to",
"match",
"a",
"long-term",
"view",
"to",
"a",
"short-term",
"view",
"of",
"the",
"same",
"video.",
"Our",
"approach,",
"named",
"Long-Short",
"Temporal",
"Contrastive",
"Learning",
"(LSTCL),",
"enables",
"video",
"transformers",
"to",
"learn",
"an",
"effective",
"clip-level",
"representation",
"by",
"predicting",
"temporal",
"context",
"captured",
"from",
"a",
"longer",
"temporal",
"extent.",
"To",
"demonstrate",
"the",
"generality",
"of",
"our",
"findings,",
"we",
"implement",
"and",
"validate",
"our",
"approach",
"under",
"three",
"different",
"self-supervised",
"contrastive",
"learning",
"frameworks",
"(MoCo",
"v3,",
"BYOL,",
"SimSiam)",
"using",
"two",
"distinct",
"video-transformer",
"architectures,",
"including",
"an",
"improved",
"variant",
"of",
"the",
"Swin",
"Transformer",
"augmented",
"with",
"space-time",
"attention.",
"We",
"conduct",
"a",
"thorough",
"ablation",
"study",
"and",
"show",
"that",
"LSTCL",
"achieves",
"competitive",
"performance",
"on",
"multiple",
"video",
"benchmarks",
"and",
"represents",
"a",
"convincing",
"alternative",
"to",
"supervised",
"image-based",
"pretraining."
] |
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[
"Object",
"detectors",
"are",
"usually",
"equipped",
"with",
"backbone",
"networks",
"designed",
"for",
"image",
"classification.",
"It",
"might",
"be",
"sub-optimal",
"because",
"of",
"the",
"gap",
"between",
"the",
"tasks",
"of",
"image",
"classification",
"and",
"object",
"detection.",
"In",
"this",
"work,",
"we",
"present",
"DetNAS",
"to",
"use",
"Neural",
"Architecture",
"Search",
"(NAS)",
"for",
"the",
"design",
"of",
"better",
"backbones",
"for",
"object",
"detection.",
"It",
"is",
"non-trivial",
"because",
"detection",
"training",
"typically",
"needs",
"ImageNet",
"pre-training",
"while",
"NAS",
"systems",
"require",
"accuracies",
"on",
"the",
"target",
"detection",
"task",
"as",
"supervisory",
"signals.",
"Based",
"on",
"the",
"technique",
"of",
"one-shot",
"supernet,",
"which",
"contains",
"all",
"possible",
"networks",
"in",
"the",
"search",
"space,",
"we",
"propose",
"a",
"framework",
"for",
"backbone",
"search",
"on",
"object",
"detection.",
"We",
"train",
"the",
"supernet",
"under",
"the",
"typical",
"detector",
"training",
"schedule:",
"ImageNet",
"pre-training",
"and",
"detection",
"fine-tuning.",
"Then,",
"the",
"architecture",
"search",
"is",
"performed",
"on",
"the",
"trained",
"supernet,",
"using",
"the",
"detection",
"task",
"as",
"the",
"guidance.",
"This",
"framework",
"makes",
"NAS",
"on",
"backbones",
"very",
"efficient.",
"In",
"experiments,",
"we",
"show",
"the",
"effectiveness",
"of",
"DetNAS",
"on",
"various",
"detectors,",
"for",
"instance,",
"one-stage",
"RetinaNet",
"and",
"the",
"two-stage",
"FPN.",
"We",
"empirically",
"find",
"that",
"networks",
"searched",
"on",
"object",
"detection",
"shows",
"consistent",
"superiority",
"compared",
"to",
"those",
"searched",
"on",
"ImageNet",
"classification.",
"The",
"resulting",
"architecture",
"achieves",
"superior",
"performance",
"than",
"hand-crafted",
"networks",
"on",
"COCO",
"with",
"much",
"less",
"FLOPs",
"complexity."
] |
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[
"The",
"overestimation",
"phenomenon",
"caused",
"by",
"function",
"approximation",
"is",
"a",
"well-known",
"issue",
"in",
"value-based",
"reinforcement",
"learning",
"algorithms",
"such",
"as",
"deep",
"Q-networks",
"and",
"DDPG,",
"which",
"could",
"lead",
"to",
"suboptimal",
"policies.",
"To",
"address",
"this",
"issue,",
"TD3",
"takes",
"the",
"minimum",
"value",
"between",
"a",
"pair",
"of",
"critics,",
"which",
"introduces",
"underestimation",
"bias.",
"By",
"unifying",
"these",
"two",
"opposites,",
"we",
"propose",
"a",
"novel",
"Weighted",
"Delayed",
"Deep",
"Deterministic",
"Policy",
"Gradient",
"algorithm,",
"which",
"can",
"reduce",
"the",
"estimation",
"error",
"and",
"further",
"improve",
"the",
"performance",
"by",
"weighting",
"a",
"pair",
"of",
"critics.",
"We",
"compare",
"the",
"learning",
"process",
"of",
"value",
"function",
"between",
"DDPG,",
"TD3",
",",
"and",
"our",
"proposed",
"algorithm,",
"which",
"verifies",
"that",
"our",
"algorithm",
"could",
"indeed",
"eliminate",
"the",
"estimation",
"error",
"of",
"value",
"function.",
"We",
"evaluate",
"our",
"algorithm",
"in",
"the",
"OpenAI",
"Gym",
"continuous",
"control",
"tasks,",
"outperforming",
"the",
"state-of-the-art",
"algorithms",
"on",
"every",
"environment",
"tested."
] |
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[
"In",
"this",
"paper",
"we",
"establish",
"a",
"duality",
"between",
"boosting",
"and",
"SVM",
",",
"and",
"use",
"this",
"to",
"derive",
"a",
"novel",
"discriminant",
"dimensionality",
"reduction",
"algorithm.",
"In",
"particular,",
"using",
"the",
"multiclass",
"formulation",
"of",
"boosting",
"and",
"SVM",
"we",
"note",
"that",
"both",
"use",
"a",
"combination",
"of",
"mapping",
"and",
"linear",
"classification",
"to",
"maximize",
"the",
"multiclass",
"margin.",
"In",
"SVM",
"this",
"is",
"implemented",
"using",
"a",
"pre-defined",
"mapping",
"(induced",
"by",
"the",
"kernel)",
"and",
"optimizing",
"the",
"linear",
"classifiers.",
"In",
"boosting",
"the",
"linear",
"classifiers",
"are",
"pre-defined",
"and",
"the",
"mapping",
"(predictor)",
"is",
"learned",
"through",
"combination",
"of",
"weak",
"learners.",
"We",
"argue",
"that",
"the",
"intermediate",
"mapping,",
"e.g.",
"boosting",
"predictor,",
"is",
"preserving",
"the",
"discriminant",
"aspects",
"of",
"the",
"data",
"and",
"by",
"controlling",
"the",
"dimension",
"of",
"this",
"mapping",
"it",
"is",
"possible",
"to",
"achieve",
"discriminant",
"low",
"dimensional",
"representations",
"for",
"the",
"data.",
"We",
"use",
"the",
"aforementioned",
"duality",
"and",
"propose",
"a",
"new",
"method,",
"Large",
"Margin",
"Discriminant",
"Dimensionality",
"Reduction",
"(LADDER)",
"that",
"jointly",
"learns",
"the",
"mapping",
"and",
"the",
"linear",
"classifiers",
"in",
"an",
"efficient",
"manner.",
"This",
"leads",
"to",
"a",
"data-driven",
"mapping",
"which",
"can",
"embed",
"data",
"into",
"any",
"number",
"of",
"dimensions.",
"Experimental",
"results",
"show",
"that",
"this",
"embedding",
"can",
"significantly",
"improve",
"performance",
"on",
"tasks",
"such",
"as",
"hashing",
"and",
"image/scene",
"classification."
] |
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[
"Time",
"Series",
"data",
"are",
"broadly",
"studied",
"in",
"various",
"domains",
"of",
"transportation",
"systems.",
"Traffic",
"data",
"area",
"challenging",
"example",
"of",
"spatio-temporal",
"data,",
"as",
"it",
"is",
"multi-variate",
"time",
"series",
"with",
"high",
"correlations",
"in",
"spatial",
"and",
"temporal",
"neighborhoods.",
"Spatio-temporal",
"clustering",
"of",
"traffic",
"flow",
"data",
"find",
"similar",
"patterns",
"in",
"both",
"spatial",
"and",
"temporal",
"domain,",
"where",
"it",
"provides",
"better",
"capability",
"for",
"analyzing",
"a",
"transportation",
"network,",
"and",
"improving",
"related",
"machine",
"learning",
"models,",
"such",
"as",
"traffic",
"flow",
"prediction",
"and",
"anomaly",
"detection.",
"In",
"this",
"paper,",
"we",
"propose",
"a",
"spatio-temporal",
"clustering",
"model,",
"where",
"it",
"clusters",
"time",
"series",
"data",
"based",
"on",
"spatial",
"and",
"temporal",
"contexts.",
"We",
"propose",
"a",
"variation",
"of",
"a",
"Deep",
"Embedded",
"Clustering(DEC)",
"model",
"for",
"finding",
"spatio-temporal",
"clusters.",
"The",
"proposed",
"model",
"Spatial-DEC",
"(S-DEC)",
"use",
"prior",
"geographical",
"information",
"in",
"building",
"latent",
"feature",
"representations.",
"We",
"also",
"define",
"evaluation",
"metrics",
"for",
"spatio-temporal",
"clusters.",
"Not",
"only",
"do",
"the",
"obtained",
"clusters",
"have",
"better",
"temporal",
"similarity",
"when",
"evaluated",
"using",
"DTW",
"distance,",
"but",
"also",
"the",
"clusters",
"better",
"represents",
"spatial",
"connectivity",
"and",
"dis-connectivity.",
"We",
"use",
"traffic",
"flow",
"data",
"obtained",
"by",
"PeMS",
"in",
"our",
"analysis.",
"The",
"results",
"show",
"that",
"the",
"proposed",
"Spatial-DEC",
"can",
"find",
"more",
"desired",
"spatio-temporal",
"clusters."
] |
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[
"In",
"this",
"paper,",
"we",
"present",
"a",
"study",
"on",
"a",
"French",
"Spoken",
"Language",
"Understanding",
"(SLU)",
"task:",
"the",
"MEDIA",
"task.",
"Many",
"works",
"and",
"studies",
"have",
"been",
"proposed",
"for",
"many",
"tasks,",
"but",
"most",
"of",
"them",
"are",
"focused",
"on",
"English",
"language",
"and",
"tasks.",
"The",
"exploration",
"of",
"a",
"richer",
"language",
"like",
"French",
"within",
"the",
"framework",
"of",
"a",
"SLU",
"task",
"implies",
"to",
"recent",
"approaches",
"to",
"handle",
"this",
"difficulty.",
"Since",
"the",
"MEDIA",
"task",
"seems",
"to",
"be",
"one",
"of",
"the",
"most",
"difficult,",
"according",
"several",
"previous",
"studies,",
"we",
"propose",
"to",
"explore",
"Neural",
"Networks",
"approaches",
"focusing",
"of",
"three",
"aspects:",
"firstly,",
"the",
"Neural",
"Network",
"inputs",
"and",
"more",
"specifically",
"the",
"word",
"embeddings;",
"secondly,",
"we",
"compared",
"French",
"version",
"of",
"BERT",
"against",
"the",
"best",
"setup",
"through",
"different",
"ways;",
"Finally,",
"the",
"comparison",
"against",
"State-of-the-Art",
"approaches.",
"Results",
"show",
"that",
"the",
"word",
"embeddings",
"trained",
"on",
"a",
"small",
"corpus",
"need",
"to",
"be",
"updated",
"during",
"SLU",
"model",
"training.",
"Furthermore,",
"the",
"French",
"BERT",
"fine-tuned",
"approaches",
"outperform",
"the",
"classical",
"Neural",
"Network",
"Architectures",
"and",
"achieves",
"state",
"of",
"the",
"art",
"results.",
"However,",
"the",
"contextual",
"embeddings",
"extracted",
"from",
"one",
"of",
"the",
"French",
"BERT",
"approaches",
"achieve",
"comparable",
"results",
"in",
"comparison",
"to",
"word",
"embedding,",
"when",
"integrated",
"into",
"the",
"proposed",
"neural",
"architecture."
] |
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[
"The",
"modern",
"artificial",
"intelligence",
"techniques",
"show",
"the",
"outstanding",
"performances",
"in",
"the",
"field",
"of",
"Non-Intrusive",
"Load",
"Monitoring",
"(NILM).",
"However,",
"the",
"problem",
"related",
"to",
"the",
"identification",
"of",
"a",
"large",
"number",
"of",
"appliances",
"working",
"simultaneously",
"is",
"underestimated.",
"One",
"of",
"the",
"reasons",
"is",
"the",
"absence",
"of",
"a",
"specific",
"data.",
"In",
"this",
"research",
"we",
"propose",
"the",
"Synthesizer",
"of",
"Normalized",
"Signatures",
"(SNS)",
"algorithm",
"to",
"simulate",
"the",
"aggregated",
"consumption",
"with",
"up",
"to",
"10",
"concurrent",
"loads.",
"The",
"results",
"show",
"that",
"the",
"synthetic",
"data",
"provides",
"the",
"models",
"with",
"at",
"least",
"as",
"a",
"powerful",
"identification",
"accuracy",
"as",
"the",
"real-world",
"measurements.",
"We",
"have",
"developed",
"the",
"neural",
"architecture",
"named",
"Concurrent",
"Loads",
"Disaggregator",
"(COLD)",
"which",
"is",
"relatively",
"simple",
"and",
"easy",
"to",
"understand",
"in",
"comparison",
"to",
"the",
"previous",
"approaches.",
"Our",
"model",
"allows",
"identifying",
"from",
"1",
"to",
"10",
"appliances",
"working",
"simultaneously",
"with",
"mean",
"F1-score",
"78.95%.",
"The",
"source",
"code",
"of",
"the",
"experiments",
"performed",
"is",
"available",
"at",
"https://github.com/arx7ti/cold-nilm."
] |
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"Recently",
"Transformer",
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[
"Learning",
"image",
"representations",
"on",
"decentralized",
"data",
"can",
"bring",
"many",
"benefits",
"in",
"cases",
"where",
"data",
"cannot",
"be",
"aggregated",
"across",
"data",
"silos.",
"Softmax",
"cross",
"entropy",
"loss",
"is",
"highly",
"effective",
"and",
"commonly",
"used",
"for",
"learning",
"image",
"representations.",
"Using",
"a",
"large",
"number",
"of",
"classes",
"has",
"proven",
"to",
"be",
"particularly",
"beneficial",
"for",
"the",
"descriptive",
"power",
"of",
"such",
"representations",
"in",
"centralized",
"learning.",
"However,",
"doing",
"so",
"on",
"decentralized",
"data",
"with",
"Federated",
"Learning",
"is",
"not",
"straightforward,",
"as",
"the",
"demand",
"on",
"computation",
"and",
"communication",
"increases",
"proportionally",
"to",
"the",
"number",
"of",
"classes.",
"In",
"this",
"work",
"we",
"introduce",
"Federated",
"Sampled",
"Softmax",
",",
"a",
"novel",
"resource-efficient",
"approach",
"for",
"learning",
"image",
"representation",
"with",
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"Learning",
".",
"Specifically,",
"the",
"FL",
"clients",
"sample",
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"set",
"of",
"negative",
"classes",
"and",
"optimize",
"only",
"the",
"corresponding",
"model",
"parameters",
"with",
"respect",
"to",
"a",
"sampled",
"softmax",
"objective",
"that",
"approximates",
"the",
"global",
"full",
"softmax",
"objective.",
"We",
"analytically",
"examine",
"the",
"loss",
"formulation",
"and",
"empirically",
"show",
"that",
"our",
"method",
"significantly",
"reduces",
"the",
"number",
"of",
"parameters",
"transferred",
"to",
"and",
"optimized",
"by",
"the",
"client",
"devices,",
"while",
"performing",
"on",
"par",
"with",
"the",
"standard",
"full",
"softmax",
"method.",
"This",
"work",
"creates",
"a",
"possibility",
"for",
"efficiently",
"learning",
"image",
"representations",
"on",
"decentralized",
"data",
"with",
"a",
"large",
"number",
"of",
"classes",
"in",
"a",
"privacy",
"preserving",
"way."
] |
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[
"Deep",
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"al",
"Neural",
"Networks",
"(DCNNs)",
"commonly",
"use",
"generic",
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"layers",
"to",
"extract",
"deformation-invariant",
"features,",
"but",
"we",
"argue",
"in",
"favor",
"ofa",
"more",
"refined",
"treatment.",
"First,",
"we",
"introduce",
"epitomic",
"convolution",
"as",
"abuilding",
"block",
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"different",
"filters,",
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"convergence",
"and",
"bettergeneralization.",
"Second,",
"we",
"introduce",
"a",
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"Learning",
"approach",
"toexplicitly",
"accommodate",
"global",
"translation",
"and",
"scaling",
"when",
"training",
"a",
"DCNNexclusively",
"with",
"class",
"labels.",
"For",
"this",
"we",
"rely",
"on",
"a",
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"data",
"structurethat",
"efficiently",
"lays",
"out",
"all",
"image",
"scales",
"and",
"positions",
"as",
"candidates",
"to",
"aDCNN.",
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"global",
"and",
"local",
"deformations",
"allows",
"a",
"DCNN",
"to",
"`focus",
"itsresources'",
"on",
"the",
"treatment",
"of",
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"deformations",
"and",
"yields",
"a",
"substantialclassification",
"accuracy",
"improvement.",
"Third,",
"further",
"pursuing",
"this",
"idea,",
"wedevelop",
"an",
"efficient",
"DCNN",
"sliding",
"window",
"object",
"detector",
"that",
"employs",
"explicitsearch",
"over",
"position,",
"scale,",
"and",
"aspect",
"ratio.",
"We",
"provide",
"competitive",
"imageclassification",
"and",
"localization",
"results",
"on",
"the",
"ImageNet",
"dataset",
"and",
"objectdetection",
"results",
"on",
"the",
"Pascal",
"VOC",
"2007",
"benchmark."
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[
"Continual",
"Learning",
"addresses",
"the",
"challenge",
"of",
"learning",
"a",
"number",
"of",
"different",
"tasks",
"sequentially.",
"The",
"goal",
"of",
"maintaining",
"knowledge",
"of",
"earlier",
"tasks",
"without",
"re-accessing",
"them",
"starkly",
"conflicts",
"with",
"standard",
"SGD",
"training",
"for",
"artificial",
"neural",
"networks.",
"An",
"influential",
"method",
"to",
"tackle",
"this",
"problem",
"without",
"storing",
"old",
"data",
"are",
"so-called",
"regularisation",
"approaches.",
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"measure",
"the",
"importance",
"of",
"each",
"parameter",
"for",
"solving",
"a",
"given",
"task",
"and",
"subsequently",
"protect",
"important",
"parameters",
"from",
"large",
"changes.",
"In",
"the",
"literature,",
"three",
"ways",
"to",
"measure",
"parameter",
"importance",
"have",
"been",
"put",
"forward",
"and",
"they",
"have",
"inspired",
"a",
"large",
"body",
"of",
"follow-up",
"work.",
"Here,",
"we",
"present",
"strong",
"theoretical",
"and",
"empirical",
"evidence",
"that",
"these",
"three",
"methods,",
"Elastic",
"Weight",
"Consolidation",
"(EWC),",
"Synaptic",
"Intelligence",
"(SI)",
"and",
"Memory",
"Aware",
"Synapses",
"(MAS),",
"are",
"surprisingly",
"similar",
"and",
"are",
"all",
"linked",
"to",
"the",
"same",
"theoretical",
"quantity.",
"Concretely,",
"we",
"show",
"that,",
"despite",
"stemming",
"from",
"very",
"different",
"motivations,",
"both",
"SI",
"and",
"MAS",
"approximate",
"the",
"square",
"root",
"of",
"the",
"Fisher",
"Information,",
"with",
"the",
"Fisher",
"being",
"the",
"theoretically",
"justified",
"basis",
"of",
"EWC.",
"Moreover,",
"we",
"show",
"that",
"for",
"SI",
"the",
"relation",
"to",
"the",
"Fisher",
"--",
"and",
"in",
"fact",
"its",
"performance",
"--",
"is",
"due",
"to",
"a",
"previously",
"unknown",
"bias.",
"On",
"top",
"of",
"uncovering",
"unknown",
"similarities",
"and",
"unifying",
"regularisation",
"approaches,",
"we",
"also",
"demonstrate",
"that",
"our",
"insights",
"enable",
"practical",
"performance",
"improvements",
"for",
"large",
"batch",
"training."
] |
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[
"Interpretability",
"techniques",
"in",
"NLP",
"have",
"mainly",
"focused",
"on",
"understanding",
"individual",
"predictions",
"using",
"attention",
"visualization",
"or",
"gradient-based",
"saliency",
"maps",
"over",
"tokens.",
"We",
"propose",
"using",
"k",
"nearest",
"neighbor",
"(kNN)",
"representations",
"to",
"identify",
"training",
"examples",
"responsible",
"for",
"a",
"model's",
"predictions",
"and",
"obtain",
"a",
"corpus-level",
"understanding",
"of",
"the",
"model's",
"behavior.",
"Apart",
"from",
"interpretability,",
"we",
"show",
"that",
"kNN",
"representations",
"are",
"effective",
"at",
"uncovering",
"learned",
"spurious",
"associations,",
"identifying",
"mislabeled",
"examples,",
"and",
"improving",
"the",
"fine-tuned",
"model's",
"performance.",
"We",
"focus",
"on",
"Natural",
"Language",
"Inference",
"(NLI)",
"as",
"a",
"case",
"study",
"and",
"experiment",
"with",
"multiple",
"datasets.",
"Our",
"method",
"deploys",
"backoff",
"to",
"kNN",
"for",
"BERT",
"and",
"RoBERTa",
"on",
"examples",
"with",
"low",
"model",
"confidence",
"without",
"any",
"update",
"to",
"the",
"model",
"parameters.",
"Our",
"results",
"indicate",
"that",
"the",
"kNN",
"approach",
"makes",
"the",
"finetuned",
"model",
"more",
"robust",
"to",
"adversarial",
"inputs."
] |
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[
"This",
"paper",
"formulates",
"a",
"new",
"task",
"of",
"extracting",
"privacy",
"parameters",
"from",
"a",
"privacy",
"policy,",
"through",
"the",
"lens",
"of",
"Contextual",
"Integrity,",
"an",
"established",
"social",
"theory",
"framework",
"for",
"reasoning",
"about",
"privacy",
"norms.",
"Privacy",
"policies,",
"written",
"by",
"lawyers,",
"are",
"lengthy",
"and",
"often",
"comprise",
"incomplete",
"and",
"vague",
"statements.",
"In",
"this",
"paper,",
"we",
"show",
"that",
"traditional",
"NLP",
"tasks,",
"including",
"the",
"recently",
"proposed",
"Question-Answering",
"based",
"solutions,",
"are",
"insufficient",
"to",
"address",
"the",
"privacy",
"parameter",
"extraction",
"problem",
"and",
"provide",
"poor",
"precision",
"and",
"recall.",
"We",
"describe",
"4",
"different",
"types",
"of",
"conventional",
"methods",
"that",
"can",
"be",
"partially",
"adapted",
"to",
"address",
"the",
"parameter",
"extraction",
"task",
"with",
"varying",
"degrees",
"of",
"success:",
"Hidden",
"Markov",
"Models,",
"BERT",
"fine-tuned",
"models,",
"Dependency",
"Type",
"Parsing",
"(DP)",
"and",
"Semantic",
"Role",
"Labeling",
"(SRL).",
"Based",
"on",
"a",
"detailed",
"evaluation",
"across",
"36",
"real-world",
"privacy",
"policies",
"of",
"major",
"enterprises,",
"we",
"demonstrate",
"that",
"a",
"solution",
"combining",
"syntactic",
"DP",
"coupled",
"with",
"type-specific",
"SRL",
"tasks",
"provides",
"the",
"highest",
"accuracy",
"for",
"retrieving",
"contextual",
"privacy",
"parameters",
"from",
"privacy",
"statements.",
"We",
"also",
"observe",
"that",
"incorporating",
"domain-specific",
"knowledge",
"is",
"critical",
"to",
"achieving",
"high",
"precision",
"and",
"recall,",
"thus",
"inspiring",
"new",
"NLP",
"research",
"to",
"address",
"this",
"important",
"problem",
"in",
"the",
"privacy",
"domain."
] |
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"assume",
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"and",
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"framework,",
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"the",
"task",
"of",
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"graph",
"context.",
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"results",
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"action",
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"a",
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"messages",
"containing",
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"dialogue",
"systems,",
"the",
"task",
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"intent",
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"adopt",
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"context",
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"history,",
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"this",
"paper,",
"we",
"demonstrate",
"the",
"limitations",
"of",
"a",
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"#NAME?",
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"model,",
"we",
"leverage",
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"intra-speaker",
"contextual",
"semantic",
"features,",
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"as",
"label",
"dependencies",
"to",
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"the",
"recognition.",
"Despite",
"extensive",
"hyper-parameter",
"optimizations,",
"this",
"architecture",
"fails",
"to",
"outperform",
"the",
"baseline",
"methods.",
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"observe",
"two",
"negative",
"results.",
"Firstly,",
"CRF",
"cannot",
"capture",
"persuasive",
"label",
"dependencies,",
"possibly",
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"strategies",
"in",
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"dialogues",
"do",
"not",
"follow",
"any",
"strict",
"grammar",
"or",
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"as",
"the",
"cases",
"in",
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"Entity",
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"(NER)",
"or",
"part-of-speech",
"(POS)",
"tagging.",
"Secondly,",
"the",
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"encoder",
"trained",
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"is",
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"capable",
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"capturing",
"sequential",
"information",
"in",
"persuasive",
"dialogues",
"than",
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"Short-Term",
"Memory",
"(LSTM).",
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"attribute",
"this",
"to",
"the",
"reason",
"that",
"the",
"vanilla",
"Transformer",
"encoder",
"does",
"not",
"efficiently",
"consider",
"relative",
"position",
"information",
"of",
"sequence",
"elements."
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",",
"NIST",
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"on",
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"of",
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".",
"Our",
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"show",
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"evaluation",
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"are",
"able",
"to",
"produce",
"useful",
"features",
"for",
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"classification",
"and",
"to",
"a",
"lesser",
"extent",
"entailment",
".",
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"gives",
"a",
"substantial",
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"in",
"paraphrase",
"classification",
"accuracy",
"over",
"all",
"of",
"the",
"other",
"models",
"used",
"in",
"the",
"experiments",
"."
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"In",
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"dialogue",
"systems,",
"the",
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"domains",
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"minutes.",
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"there",
"are",
"domains",
"that",
"have",
"related",
"context",
"that",
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"span",
"up",
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"and",
"days.",
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"this",
"paper,",
"we",
"propose",
"temporal",
"representations",
"that",
"combine",
"wall-clock",
"second",
"difference",
"and",
"turn",
"order",
"offset",
"information",
"to",
"utilize",
"both",
"recent",
"and",
"distant",
"context",
"in",
"a",
"novel",
"large-scale",
"setup.",
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"on",
"the",
"Contextual",
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"Classification",
"(CDC)",
"task",
"with",
"various",
"encoder",
"architectures",
"show",
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"temporal",
"representations",
"combining",
"both",
"information",
"outperforms",
"only",
"one",
"of",
"the",
"two.",
"We",
"further",
"demonstrate",
"that",
"our",
"contextual",
"Transformer",
"is",
"able",
"to",
"reduce",
"13.04{\\%}",
"of",
"classification",
"errors",
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"to",
"a",
"non-contextual",
"baseline.",
"We",
"also",
"conduct",
"empirical",
"analyses",
"to",
"study",
"recent",
"versus",
"distant",
"context",
"and",
"opportunities",
"to",
"lower",
"deployment",
"costs."
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"Semantic",
"Role",
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"(SRL)",
"is",
"a",
"core",
"Natural",
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"Processing",
"task.",
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"English,",
"recent",
"methods",
"based",
"on",
"Transformer",
"models",
"have",
"allowed",
"for",
"major",
"improvements",
"over",
"the",
"previous",
"state",
"of",
"the",
"art.",
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"for",
"low",
"resource",
"languages,",
"and",
"in",
"particular",
"for",
"Portuguese,",
"currently",
"available",
"SRL",
"models",
"are",
"hindered",
"by",
"scarce",
"training",
"data.",
"In",
"this",
"paper,",
"we",
"explore",
"a",
"model",
"architecture",
"with",
"only",
"a",
"pre-trained",
"BERT-based",
"model,",
"a",
"linear",
"layer,",
"softmax",
"and",
"Viterbi",
"decoding.",
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"substantially",
"improve",
"the",
"state",
"of",
"the",
"art",
"performance",
"in",
"Portuguese",
"by",
"over",
"15$F_1$.",
"Additionally,",
"we",
"improve",
"SRL",
"results",
"in",
"Portuguese",
"corpora",
"by",
"exploiting",
"cross-lingual",
"transfer",
"learning",
"using",
"multilingual",
"pre-trained",
"models",
"(XLM-R),",
"and",
"transfer",
"learning",
"from",
"dependency",
"parsing",
"in",
"Portuguese.",
"We",
"evaluate",
"the",
"various",
"proposed",
"approaches",
"empirically",
"and",
"as",
"result",
"we",
"present",
"an",
"heuristic",
"that",
"supports",
"the",
"choice",
"of",
"the",
"most",
"appropriate",
"model",
"considering",
"the",
"available",
"resources."
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[
"Recently,",
"deep",
"neural",
"networks",
"(DNNs)",
"have",
"achieved",
"great",
"success",
"in",
"semantically",
"challenging",
"NLP",
"tasks,",
"yet",
"it",
"remains",
"unclear",
"whether",
"DNN",
"models",
"can",
"capture",
"compositional",
"meanings,",
"those",
"aspects",
"of",
"meaning",
"that",
"have",
"been",
"long",
"studied",
"in",
"formal",
"semantics.",
"To",
"investigate",
"this",
"issue,",
"we",
"propose",
"a",
"Systematic",
"Generalization",
"testbed",
"based",
"on",
"Natural",
"language",
"Semantics",
"(SyGNS),",
"whose",
"challenge",
"is",
"to",
"map",
"natural",
"language",
"sentences",
"to",
"multiple",
"forms",
"of",
"scoped",
"meaning",
"representations,",
"designed",
"to",
"account",
"for",
"various",
"semantic",
"phenomena.",
"Using",
"SyGNS,",
"we",
"test",
"whether",
"neural",
"networks",
"can",
"systematically",
"parse",
"sentences",
"involving",
"novel",
"combinations",
"of",
"logical",
"expressions",
"such",
"as",
"quantifiers",
"and",
"negation.",
"Experiments",
"show",
"that",
"Transformer",
"and",
"GRU",
"models",
"can",
"generalize",
"to",
"unseen",
"combinations",
"of",
"quantifiers,",
"negations,",
"and",
"modifiers",
"that",
"are",
"similar",
"to",
"given",
"training",
"instances",
"in",
"form,",
"but",
"not",
"to",
"the",
"others.",
"We",
"also",
"find",
"that",
"the",
"generalization",
"performance",
"to",
"unseen",
"combinations",
"is",
"better",
"when",
"the",
"form",
"of",
"meaning",
"representations",
"is",
"simpler.",
"The",
"data",
"and",
"code",
"for",
"SyGNS",
"are",
"publicly",
"available",
"at",
"https://github.com/verypluming/SyGNS."
] |
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[
"Neural",
"architecture",
"search",
"(NAS)",
"recently",
"attracts",
"much",
"research",
"attention",
"because",
"of",
"its",
"ability",
"to",
"identify",
"better",
"architectures",
"than",
"handcrafted",
"ones.",
"However,",
"many",
"NAS",
"methods,",
"which",
"optimize",
"the",
"search",
"process",
"in",
"a",
"discrete",
"search",
"space,",
"need",
"many",
"GPU",
"days",
"for",
"convergence.",
"Recently,",
"DARTS",
",",
"which",
"constructs",
"a",
"differentiable",
"search",
"space",
"and",
"then",
"optimizes",
"it",
"by",
"gradient",
"descent,",
"can",
"obtain",
"high-performance",
"architecture",
"and",
"reduces",
"the",
"search",
"time",
"to",
"several",
"days.",
"However,",
"DARTS",
"is",
"still",
"slow",
"as",
"it",
"updates",
"an",
"ensemble",
"of",
"all",
"operations",
"and",
"keeps",
"only",
"one",
"after",
"convergence.",
"Besides,",
"DARTS",
"can",
"converge",
"to",
"inferior",
"architectures",
"due",
"to",
"the",
"strong",
"correlation",
"among",
"operations.",
"In",
"this",
"paper,",
"we",
"propose",
"a",
"new",
"differentiable",
"Neural",
"Architecture",
"Search",
"method",
"based",
"on",
"Proximal",
"gradient",
"descent",
"(denoted",
"as",
"NASP).",
"Different",
"from",
"DARTS",
",",
"NASP",
"reformulates",
"the",
"search",
"process",
"as",
"an",
"optimization",
"problem",
"with",
"a",
"constraint",
"that",
"only",
"one",
"operation",
"is",
"allowed",
"to",
"be",
"updated",
"during",
"forward",
"and",
"backward",
"propagation.",
"Since",
"the",
"constraint",
"is",
"hard",
"to",
"deal",
"with,",
"we",
"propose",
"a",
"new",
"algorithm",
"inspired",
"by",
"proximal",
"iterations",
"to",
"solve",
"it.",
"Experiments",
"on",
"various",
"tasks",
"demonstrate",
"that",
"NASP",
"can",
"obtain",
"high-performance",
"architectures",
"with",
"10",
"times",
"of",
"speedup",
"on",
"the",
"computational",
"time",
"than",
"DARTS",
"."
] |
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[
"This",
"study",
"aims",
"at",
"solving",
"the",
"Machine",
"Reading",
"Comprehension",
"problem",
"wherequestions",
"have",
"to",
"be",
"answered",
"given",
"a",
"context",
"passage.",
"The",
"challenge",
"is",
"todevelop",
"a",
"computationally",
"faster",
"model",
"which",
"will",
"have",
"improved",
"inference",
"time.State",
"of",
"the",
"art",
"in",
"many",
"natural",
"language",
"understanding",
"tasks,",
"BERT",
"model,",
"hasbeen",
"used",
"and",
"knowledge",
"distillation",
"method",
"has",
"been",
"applied",
"to",
"train",
"twosmaller",
"models.",
"The",
"developed",
"models",
"are",
"compared",
"with",
"other",
"models",
"which",
"havebeen",
"developed",
"with",
"the",
"same",
"intention."
] |
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[
"We",
"investigate",
"adversarial",
"robustness",
"of",
"Gaussian",
"Process",
"Classification",
"(GPC)",
"models.",
"Given",
"a",
"compact",
"subset",
"of",
"the",
"input",
"space",
"$T\\subseteq",
"\\mathbb{R}^d$",
"enclosing",
"a",
"test",
"point",
"$x^*$",
"and",
"a",
"GPC",
"trained",
"on",
"a",
"dataset",
"$\\mathcal{D}$,",
"we",
"aim",
"to",
"compute",
"the",
"minimum",
"and",
"the",
"maximum",
"classification",
"probability",
"for",
"the",
"GPC",
"over",
"all",
"the",
"points",
"in",
"$T$.",
"In",
"order",
"to",
"do",
"so,",
"we",
"show",
"how",
"functions",
"lower-",
"and",
"upper-bounding",
"the",
"GPC",
"output",
"in",
"$T$",
"can",
"be",
"derived,",
"and",
"implement",
"those",
"in",
"a",
"branch",
"and",
"bound",
"optimisation",
"algorithm.",
"For",
"any",
"error",
"threshold",
"$\\epsilon",
">",
"0$",
"selected",
"a",
"priori,",
"we",
"show",
"that",
"our",
"algorithm",
"is",
"guaranteed",
"to",
"reach",
"values",
"$\\epsilon$-close",
"to",
"the",
"actual",
"values",
"in",
"finitely",
"many",
"iterations.",
"We",
"apply",
"our",
"method",
"to",
"investigate",
"the",
"robustness",
"of",
"GPC",
"models",
"on",
"a",
"2D",
"synthetic",
"dataset,",
"the",
"SPAM",
"dataset",
"and",
"a",
"subset",
"of",
"the",
"MNIST",
"dataset,",
"providing",
"comparisons",
"of",
"different",
"GPC",
"training",
"techniques,",
"and",
"show",
"how",
"our",
"method",
"can",
"be",
"used",
"for",
"interpretability",
"analysis.",
"Our",
"empirical",
"analysis",
"suggests",
"that",
"GPC",
"robustness",
"increases",
"with",
"more",
"accurate",
"posterior",
"estimation."
] |
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[
"This",
"work",
"includes",
"all",
"the",
"technical",
"details",
"of",
"the",
"Sequential",
"PrincipalCurves",
"Analysis",
"(SPCA",
")",
"in",
"a",
"single",
"document.",
"SPCA",
"is",
"an",
"unsupervised",
"nonlinearand",
"invertible",
"feature",
"extraction",
"technique.",
"The",
"identified",
"curvilinearfeatures",
"can",
"be",
"interpreted",
"as",
"a",
"set",
"of",
"nonlinear",
"sensors:",
"the",
"response",
"of",
"eachsensor",
"is",
"the",
"projection",
"onto",
"the",
"corresponding",
"feature.",
"Moreover,",
"it",
"can",
"beeasily",
"tuned",
"for",
"different",
"optimization",
"criteria;",
"e.g.",
"infomax,",
"errorminimization,",
"decorrelation;",
"by",
"choosing",
"the",
"right",
"way",
"to",
"measure",
"distancesalong",
"each",
"curvilinear",
"feature.",
"Even",
"though",
"proposed",
"in",
"[Laparra",
"et",
"al.",
"NeuralComp.",
"12]",
"and",
"shown",
"to",
"work",
"in",
"multiple",
"modalities",
"in",
"[Laparra",
"and",
"MaloFrontiers",
"Hum.",
"Neuro.",
"15],",
"the",
"SPCA",
"framework",
"has",
"its",
"original",
"roots",
"in",
"thenonlinear",
"ICA",
"algorithm",
"in",
"[Malo",
"and",
"Gutierrez",
"Network",
"06].",
"Later",
"on,",
"the",
"SPCA",
"philosophy",
"for",
"nonlinear",
"generalization",
"of",
"PCA",
"originated",
"substantially",
"fasteralternatives",
"at",
"the",
"cost",
"of",
"introducing",
"different",
"constraints",
"in",
"the",
"model.Namely,",
"the",
"Principal",
"Polynomial",
"Analysis",
"(PPA)",
"[Laparra",
"et",
"al.",
"IJNS",
"14],",
"andthe",
"Dimensionality",
"Reduction",
"via",
"Regression",
"(DRR)",
"[Laparra",
"et",
"al.",
"IEEE",
"TGRS15].",
"This",
"report",
"illustrates",
"the",
"reasons",
"why",
"we",
"developed",
"such",
"family",
"and",
"isthe",
"appropriate",
"technical",
"companion",
"for",
"the",
"missing",
"details",
"in",
"[Laparra",
"et",
"al.,NeCo",
"12,",
"Laparra",
"and",
"Malo,",
"Front.Hum.Neuro.",
"15].",
"See",
"also",
"the",
"data,",
"code",
"andexamples",
"in",
"the",
"dedicated",
"sites",
"http://isp.uv.es/spca.html",
"andhttp://isp.uv.es/after",
"effects.html"
] |
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[
"In",
"light",
"of",
"the",
"recent",
"breakthroughs",
"in",
"automatic",
"machine",
"translation",
"systems,",
"we",
"propose",
"a",
"novel",
"approach",
"that",
"we",
"term",
"as",
"Face-to-Face\tO\nTranslation\tS-RESEARCH_PROBLEM\n.",
"As",
"today's",
"digital",
"communication",
"becomes",
"increasingly",
"visual,",
"we",
"argue",
"that",
"there",
"is",
"a",
"need",
"for",
"systems",
"that",
"can",
"automatically",
"translate",
"a",
"video",
"of",
"a",
"person",
"speaking",
"in",
"language",
"A",
"into",
"a",
"target",
"language",
"B",
"with",
"realistic",
"lip",
"synchronization.",
"In",
"this",
"work,",
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[
"We",
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"can",
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"prediction,",
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"backbone",
"(LCB)",
"and",
"lightweight",
"Transformer",
"backbone",
"(LTB).",
"Among",
"them,",
"LCB",
"is",
"a",
"lightweight",
"SR",
"network",
"to",
"extract",
"deep",
"SR",
"features",
"at",
"a",
"low",
"computational",
"cost",
"by",
"dynamically",
"adjusting",
"the",
"size",
"of",
"the",
"feature",
"map.",
"LTB",
"is",
"made",
"up",
"of",
"an",
"efficient",
"Transformer",
"(ET)",
"with",
"a",
"small",
"GPU",
"memory",
"occupation,",
"which",
"benefited",
"from",
"the",
"novel",
"efficient",
"multi-head",
"attention",
"(EMHA).",
"In",
"EMHA,",
"a",
"feature",
"split",
"module",
"(FSM)",
"is",
"proposed",
"to",
"split",
"the",
"long",
"sequence",
"into",
"sub-segments",
"and",
"then",
"these",
"sub-segments",
"are",
"applied",
"by",
"attention",
"operation.",
"This",
"module",
"can",
"significantly",
"decrease",
"the",
"GPU",
"memory",
"occupation.",
"Extensive",
"experiments",
"show",
"that",
"our",
"ESRT",
"achieves",
"competitive",
"results.",
"Compared",
"with",
"the",
"original",
"Transformer",
"which",
"occupies",
"16057M",
"GPU",
"memory,",
"the",
"proposed",
"ET",
"only",
"occupies",
"4191M",
"GPU",
"memory",
"with",
"better",
"performance."
] |
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[
"Establishing",
"associations",
"between",
"the",
"structure",
"and",
"the",
"generalisation",
"ability",
"of",
"deep",
"neural",
"networks",
"(DNNs)",
"is",
"a",
"challenging",
"task",
"in",
"modern",
"machine",
"learning.",
"Producing",
"solutions",
"to",
"this",
"challenge",
"will",
"bring",
"progress",
"both",
"in",
"the",
"theoretical",
"understanding",
"of",
"DNNs",
"and",
"in",
"building",
"new",
"architectures",
"efficiently.",
"In",
"this",
"work,",
"we",
"address",
"this",
"challenge",
"by",
"developing",
"a",
"new",
"complexity",
"measure",
"based",
"on",
"the",
"concept",
"of",
"{Periodic",
"Spectral",
"Ergodicity}",
"(PSE)",
"originating",
"from",
"quantum",
"statistical",
"mechanics.",
"Based",
"on",
"this",
"measure",
"a",
"technique",
"is",
"devised",
"to",
"quantify",
"the",
"complexity",
"of",
"deep",
"neural",
"networks",
"from",
"the",
"learned",
"weights",
"and",
"traversing",
"the",
"network",
"connectivity",
"in",
"a",
"sequential",
"manner,",
"hence",
"the",
"term",
"cascading",
"PSE",
"(cPSE),",
"as",
"an",
"empirical",
"complexity",
"measure.",
"This",
"measure",
"will",
"capture",
"both",
"topological",
"and",
"internal",
"neural",
"processing",
"complexity",
"simultaneously.",
"Because",
"of",
"this",
"cascading",
"approach,",
"i.e.,",
"a",
"symmetric",
"divergence",
"of",
"PSE",
"on",
"the",
"consecutive",
"layers,",
"it",
"is",
"possible",
"to",
"use",
"this",
"measure",
"for",
"Neural",
"Architecture",
"Search",
"(NAS).",
"We",
"demonstrate",
"the",
"usefulness",
"of",
"this",
"measure",
"in",
"practice",
"on",
"two",
"sets",
"of",
"vision",
"models,",
"ResNet",
"and",
"VGG,",
"and",
"sketch",
"the",
"computation",
"of",
"cPSE",
"for",
"more",
"complex",
"network",
"structures."
] |
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[
"In",
"the",
"field",
"of",
"multi-objective",
"optimization",
"algorithms,",
"multi-objective",
"Bayesian",
"Global",
"Optimization",
"(MOBGO)",
"is",
"an",
"important",
"branch,",
"in",
"addition",
"to",
"evolutionary",
"multi-objective",
"optimization",
"algorithms",
"(EMOAs).",
"MOBGO",
"utilizes",
"Gaussian",
"Process",
"models",
"learned",
"from",
"previous",
"objective",
"function",
"evaluations",
"to",
"decide",
"the",
"next",
"evaluation",
"site",
"by",
"maximizing",
"or",
"minimizing",
"an",
"infill",
"criterion.",
"A",
"common",
"criterion",
"in",
"MOBGO",
"is",
"the",
"Expected",
"Hypervolume",
"Improvement",
"(EHVI),",
"which",
"shows",
"a",
"good",
"performance",
"on",
"a",
"wide",
"range",
"of",
"problems,",
"with",
"respect",
"to",
"exploration",
"and",
"exploitation.",
"However,",
"so",
"far",
"it",
"has",
"been",
"a",
"challenge",
"to",
"calculate",
"exact",
"EHVI",
"values",
"efficiently.",
"In",
"this",
"paper,",
"an",
"efficient",
"algorithm",
"for",
"the",
"computation",
"of",
"the",
"exact",
"EHVI",
"for",
"a",
"generic",
"case",
"is",
"proposed.",
"This",
"efficient",
"algorithm",
"is",
"based",
"on",
"partitioning",
"the",
"integration",
"volume",
"into",
"a",
"set",
"of",
"axis-parallel",
"slices.",
"Theoretically,",
"the",
"upper",
"bound",
"time",
"complexities",
"are",
"improved",
"from",
"previously",
"$O",
"(n^2)$",
"and",
"$O(n^3)$,",
"for",
"two-",
"and",
"three-objective",
"problems",
"respectively,",
"to",
"$\\Theta(n\\log",
"n)$,",
"which",
"is",
"asymptotically",
"optimal.",
"This",
"article",
"generalizes",
"the",
"scheme",
"in",
"higher",
"dimensional",
"case",
"by",
"utilizing",
"a",
"new",
"hyperbox",
"decomposition",
"technique,",
"which",
"was",
"proposed",
"by",
"D{\\\"a}chert",
"et",
"al,",
"EJOR,",
"2017",
"It",
"also",
"utilizes",
"a",
"generalization",
"of",
"the",
"multilayered",
"integration",
"scheme",
"that",
"scales",
"linearly",
"in",
"the",
"number",
"of",
"hyperboxes",
"of",
"the",
"decomposition.",
"The",
"speed",
"comparison",
"shows",
"that",
"the",
"proposed",
"algorithm",
"in",
"this",
"paper",
"significantly",
"reduces",
"computation",
"time.",
"Finally,",
"this",
"decomposition",
"technique",
"is",
"applied",
"in",
"the",
"calculation",
"of",
"the",
"Probability",
"of",
"Improvement",
"(PoI)."
] |
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[
"We",
"propose",
"a",
"novel",
"pool-based",
"Active",
"Learning",
"framework",
"constructed",
"on",
"a",
"sequential",
"Graph",
"Convolution",
"Network",
"(GCN",
").",
"Each",
"image's",
"feature",
"from",
"a",
"pool",
"of",
"data",
"represents",
"a",
"node",
"in",
"the",
"graph",
"and",
"the",
"edges",
"encode",
"their",
"similarities.",
"With",
"a",
"small",
"number",
"of",
"randomly",
"sampled",
"images",
"as",
"seed",
"labelled",
"examples,",
"we",
"learn",
"the",
"parameters",
"of",
"the",
"graph",
"to",
"distinguish",
"labelled",
"vs",
"unlabelled",
"nodes",
"by",
"minimising",
"the",
"binary",
"cross-entropy",
"loss.",
"GCN",
"performs",
"message-passing",
"operations",
"between",
"the",
"nodes,",
"and",
"hence,",
"induces",
"similar",
"representations",
"of",
"the",
"strongly",
"associated",
"nodes.",
"We",
"exploit",
"these",
"characteristics",
"of",
"GCN",
"to",
"select",
"the",
"unlabelled",
"examples",
"which",
"are",
"sufficiently",
"different",
"from",
"labelled",
"ones.",
"To",
"this",
"end,",
"we",
"utilise",
"the",
"graph",
"node",
"embeddings",
"and",
"their",
"confidence",
"scores",
"and",
"adapt",
"sampling",
"techniques",
"such",
"as",
"CoreSet",
"and",
"uncertainty-based",
"methods",
"to",
"query",
"the",
"nodes.",
"We",
"flip",
"the",
"label",
"of",
"newly",
"queried",
"nodes",
"from",
"unlabelled",
"to",
"labelled,",
"re-train",
"the",
"learner",
"to",
"optimise",
"the",
"downstream",
"task",
"and",
"the",
"graph",
"to",
"minimise",
"its",
"modified",
"objective.",
"We",
"continue",
"this",
"process",
"within",
"a",
"fixed",
"budget.",
"We",
"evaluate",
"our",
"method",
"on",
"6",
"different",
"benchmarks:4",
"real",
"image",
"classification,",
"1",
"depth-based",
"hand",
"pose",
"estimation",
"and",
"1",
"synthetic",
"RGB",
"image",
"classification",
"datasets.",
"Our",
"method",
"outperforms",
"several",
"competitive",
"baselines",
"such",
"as",
"VAAL,",
"Learning",
"Loss,",
"CoreSet",
"and",
"attains",
"the",
"new",
"state-of-the-art",
"performance",
"on",
"multiple",
"applications",
"The",
"implementations",
"can",
"be",
"found",
"here:",
"https://github.com/razvancaramalau/Sequential-GCN",
"#NAME?"
] |
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[
"Abnormal",
"activity",
"detection",
"is",
"one",
"of",
"the",
"most",
"challenging",
"tasks",
"in",
"the",
"field",
"of",
"computer",
"vision.",
"This",
"study",
"is",
"motivated",
"by",
"the",
"recent",
"state-of-art",
"work",
"of",
"abnormal",
"activity",
"detection,",
"which",
"utilizes",
"both",
"abnormal",
"and",
"normal",
"videos",
"in",
"learning",
"abnormalities",
"with",
"the",
"help",
"of",
"multiple",
"instance",
"learning",
"by",
"providing",
"the",
"data",
"with",
"video-level",
"information.",
"In",
"the",
"absence",
"of",
"temporal-annotations,",
"such",
"a",
"model",
"is",
"prone",
"to",
"give",
"a",
"FALSE",
"alarm",
"while",
"detecting",
"the",
"abnormalities.",
"For",
"this",
"reason,",
"in",
"this",
"paper,",
"we",
"focus",
"on",
"the",
"task",
"of",
"minimizing",
"the",
"FALSE",
"alarm",
"rate",
"while",
"performing",
"an",
"abnormal",
"activity",
"detection",
"task.",
"The",
"mitigation",
"of",
"these",
"FALSE",
"alarms",
"and",
"recent",
"advancement",
"of",
"3D",
"deep",
"neural",
"network",
"in",
"video",
"action",
"recognition",
"task",
"collectively",
"give",
"us",
"motivation",
"to",
"exploit",
"the",
"3D",
"ResNet",
"in",
"our",
"proposed",
"method,",
"which",
"helps",
"to",
"extract",
"spatial-temporal",
"features",
"from",
"the",
"videos.",
"Afterwards,",
"using",
"these",
"features",
"and",
"deep",
"multiple",
"instance",
"learning",
"along",
"with",
"the",
"proposed",
"ranking",
"loss,",
"our",
"model",
"learns",
"to",
"predict",
"the",
"abnormality",
"score",
"at",
"the",
"video",
"segment",
"level.",
"Therefore,",
"our",
"proposed",
"method",
"3D",
"deep",
"Multiple",
"Instance",
"Learning",
"with",
"ResNet",
"(MILR)",
"along",
"with",
"the",
"new",
"proposed",
"ranking",
"loss",
"function",
"achieves",
"the",
"best",
"performance",
"on",
"the",
"UCF-Crime",
"benchmark",
"dataset,",
"as",
"compared",
"to",
"other",
"state-of-art",
"methods.",
"The",
"effectiveness",
"of",
"our",
"proposed",
"method",
"is",
"demonstrated",
"on",
"the",
"UCF-Crime",
"dataset."
] |
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[
"Documents",
"often",
"contain",
"complex",
"physical",
"structures,",
"which",
"make",
"the",
"Document",
"Layout",
"Analysis",
"(DLA",
")",
"task",
"challenging.",
"As",
"a",
"pre-processing",
"step",
"for",
"content",
"extraction,",
"DLA",
"has",
"the",
"potential",
"to",
"capture",
"rich",
"information",
"in",
"historical",
"or",
"scientific",
"documents",
"on",
"a",
"large",
"scale.",
"Although",
"many",
"deep-learning-based",
"methods",
"from",
"computer",
"vision",
"have",
"already",
"achieved",
"excellent",
"performance",
"in",
"detecting",
"\\emph{Figure}",
"from",
"documents,",
"they",
"are",
"still",
"unsatisfactory",
"in",
"recognizing",
"the",
"\\emph{List},",
"\\emph{Table},",
"\\emph{Text}",
"and",
"\\emph{Title}",
"category",
"blocks",
"in",
"DLA",
".",
"This",
"paper",
"proposes",
"a",
"VTLayout",
"model",
"fusing",
"the",
"documents'",
"deep",
"visual,",
"shallow",
"visual,",
"and",
"text",
"features",
"to",
"localize",
"and",
"identify",
"different",
"category",
"blocks.",
"The",
"model",
"mainly",
"includes",
"two",
"stages,",
"and",
"the",
"three",
"feature",
"extractors",
"are",
"built",
"in",
"the",
"second",
"stage.",
"In",
"the",
"first",
"stage,",
"the",
"Cascade",
"Mask",
"R-CNN",
"model",
"is",
"applied",
"directly",
"to",
"localize",
"all",
"category",
"blocks",
"of",
"the",
"documents.",
"In",
"the",
"second",
"stage,",
"the",
"deep",
"visual,",
"shallow",
"visual,",
"and",
"text",
"features",
"are",
"extracted",
"for",
"fusion",
"to",
"identify",
"the",
"category",
"blocks",
"of",
"documents.",
"As",
"a",
"result,",
"we",
"strengthen",
"the",
"classification",
"power",
"of",
"different",
"category",
"blocks",
"based",
"on",
"the",
"existing",
"localization",
"technique.",
"The",
"experimental",
"results",
"show",
"that",
"the",
"identification",
"capability",
"of",
"the",
"VTLayout",
"is",
"superior",
"to",
"the",
"most",
"advanced",
"method",
"of",
"DLA",
"based",
"on",
"the",
"PubLayNet",
"dataset,",
"and",
"the",
"F1",
"score",
"is",
"as",
"high",
"as",
"0.9599."
] |
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[
"In",
"this",
"paper,",
"we",
"particularly",
"work",
"on",
"the",
"code-switched",
"text,",
"one",
"of",
"the",
"most",
"common",
"occurrences",
"in",
"the",
"bilingual",
"communities",
"across",
"the",
"world.",
"Due",
"to",
"the",
"discrepancies",
"in",
"the",
"extraction",
"of",
"code-switched",
"text",
"from",
"an",
"Automated",
"Speech",
"Recognition(ASR)",
"module,",
"and",
"thereby",
"extracting",
"the",
"monolingual",
"text",
"from",
"the",
"code-switched",
"text,",
"we",
"propose",
"an",
"approach",
"for",
"extracting",
"monolingual",
"text",
"using",
"Deep",
"Bi-directional",
"Language",
"Models(LM)",
"such",
"as",
"BERT",
"and",
"other",
"Machine",
"Translation",
"models,",
"and",
"also",
"explore",
"different",
"ways",
"of",
"extracting",
"code-switched",
"text",
"from",
"the",
"ASR",
"model.",
"We",
"also",
"explain",
"the",
"robustness",
"of",
"the",
"model",
"by",
"comparing",
"the",
"results",
"of",
"Perplexity",
"and",
"other",
"different",
"metrics",
"like",
"WER,",
"to",
"the",
"standard",
"bi-lingual",
"text",
"output",
"without",
"any",
"external",
"information."
] |
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[
"Cellular",
"and",
"molecular",
"imaging",
"techniques",
"and",
"models",
"have",
"been",
"developed",
"to",
"characterize",
"single",
"stages",
"of",
"viral",
"proliferation",
"after",
"focal",
"infection",
"of",
"cells",
"in",
"vitro.",
"The",
"fast",
"and",
"automatic",
"classification",
"of",
"cell",
"imaging",
"data",
"may",
"prove",
"helpful",
"prior",
"to",
"any",
"further",
"comparison",
"of",
"representative",
"experimental",
"data",
"to",
"mathematical",
"models",
"of",
"viral",
"propagation",
"in",
"host",
"cells.",
"Here,",
"we",
"use",
"computer",
"generated",
"images",
"drawn",
"from",
"a",
"reproduction",
"of",
"an",
"imaging",
"model",
"from",
"a",
"previously",
"published",
"study",
"of",
"experimentally",
"obtained",
"cell",
"imaging",
"data",
"representing",
"progressive",
"viral",
"particle",
"proliferation",
"in",
"host",
"cell",
"monolayers.",
"Inspired",
"by",
"experimental",
"time-based",
"imaging",
"data,",
"here",
"in",
"this",
"study",
"viral",
"particle",
"increase",
"in",
"time",
"is",
"simulated",
"by",
"a",
"one-by-one",
"increase,",
"across",
"images,",
"in",
"black",
"or",
"gray",
"single",
"pixels",
"representing",
"dead",
"or",
"partially",
"infected",
"cells,",
"and",
"hypothetical",
"remission",
"by",
"a",
"one-by-one",
"increase",
"in",
"white",
"pixels",
"coding",
"for",
"living",
"cells",
"in",
"the",
"original",
"image",
"model.",
"The",
"image",
"simulations",
"are",
"submitted",
"to",
"unsupervised",
"learning",
"by",
"a",
"Self-Organizing",
"Map",
"(SOM",
")",
"and",
"the",
"Quantization",
"Error",
"in",
"the",
"SOM",
"output",
"(SOM",
"-QE)",
"is",
"used",
"for",
"automatic",
"classification",
"of",
"the",
"image",
"simulations",
"as",
"a",
"function",
"of",
"the",
"represented",
"extent",
"of",
"viral",
"particle",
"proliferation",
"or",
"cell",
"recovery.",
"Unsupervised",
"classification",
"by",
"SOM",
"#NAME?",
"of",
"160",
"model",
"images,",
"each",
"with",
"more",
"than",
"three",
"million",
"pixels,",
"is",
"shown",
"to",
"provide",
"a",
"statistically",
"reliable,",
"pixel",
"precise,",
"and",
"fast",
"classification",
"model",
"that",
"outperforms",
"human",
"computer-assisted",
"image",
"classification",
"by",
"RGB",
"image",
"mean",
"computation.",
"The",
"automatic",
"classification",
"procedure",
"proposed",
"here",
"provides",
"a",
"powerful",
"approach",
"to",
"understand",
"finely",
"tuned",
"mechanisms",
"in",
"the",
"infection",
"and",
"proliferation",
"of",
"virus",
"in",
"cell",
"lines",
"in",
"vitro",
"or",
"other",
"cells."
] |
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[
"The",
"quality",
"of",
"automatic",
"speech",
"recognition",
"(ASR)",
"is",
"critical",
"to",
"Dialogue",
"Systems",
"as",
"ASR",
"errors",
"propagate",
"to",
"and",
"directly",
"impact",
"downstream",
"tasks",
"such",
"as",
"language",
"understanding",
"(LU).",
"In",
"this",
"paper,",
"we",
"propose",
"multi-task",
"neural",
"approaches",
"to",
"perform",
"contextual",
"language",
"correction",
"on",
"ASR",
"outputs",
"jointly",
"with",
"LU",
"to",
"improve",
"the",
"performance",
"of",
"both",
"tasks",
"simultaneously.",
"To",
"measure",
"the",
"effectiveness",
"of",
"this",
"approach",
"we",
"used",
"a",
"public",
"benchmark,",
"the",
"2nd",
"Dialogue",
"State",
"Tracking",
"(DSTC2)",
"corpus.",
"As",
"a",
"baseline",
"approach,",
"we",
"trained",
"task-specific",
"Statistical",
"Language",
"Models",
"(SLM)",
"and",
"fine-tuned",
"state-of-the-art",
"Generalized",
"Pre-training",
"(GPT",
")",
"Language",
"Model",
"to",
"re-rank",
"the",
"n-best",
"ASR",
"hypotheses,",
"followed",
"by",
"a",
"model",
"to",
"identify",
"the",
"dialog",
"act",
"and",
"slots.",
"i)",
"We",
"further",
"trained",
"ranker",
"models",
"using",
"GPT",
"and",
"Hierarchical",
"CNN-RNN",
"models",
"with",
"discriminatory",
"losses",
"to",
"detect",
"the",
"best",
"output",
"given",
"n-best",
"hypotheses.",
"We",
"extended",
"these",
"ranker",
"models",
"to",
"first",
"select",
"the",
"best",
"ASR",
"output",
"and",
"then",
"identify",
"the",
"dialogue",
"act",
"and",
"slots",
"in",
"an",
"end",
"to",
"end",
"fashion.",
"ii)",
"We",
"also",
"proposed",
"a",
"novel",
"joint",
"ASR",
"error",
"correction",
"and",
"LU",
"model,",
"a",
"word",
"confusion",
"pointer",
"network",
"(WCN-Ptr)",
"with",
"multi-head",
"self-attention",
"on",
"top,",
"which",
"consumes",
"the",
"word",
"confusions",
"populated",
"from",
"the",
"n-best.",
"We",
"show",
"that",
"the",
"error",
"rates",
"of",
"off",
"the",
"shelf",
"ASR",
"and",
"following",
"LU",
"systems",
"can",
"be",
"reduced",
"significantly",
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"14%",
"relative",
"with",
"joint",
"models",
"trained",
"using",
"small",
"amounts",
"of",
"in-domain",
"data."
] |
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"This",
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",",
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"corpus",
"providing",
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"operations,",
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"dimensions",
"to",
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"economic",
"loss",
"and",
"fatalities),",
"we",
"fit",
"a",
"multi-linear",
"regression",
"model",
"to",
"quantify",
"the",
"overall",
"damage.",
"To",
"validate",
"our",
"combined",
"system",
"of",
"deep",
"learning",
"and",
"regression",
"modeling,",
"we",
"successfully",
"match",
"our",
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"recovery",
"in",
"the",
"2020",
"Beirut",
"port",
"explosion.",
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"provide",
"a",
"better",
"quantification",
"of",
"overall",
"disaster",
"magnitude",
"and",
"inform",
"intelligent",
"humanitarian",
"systems",
"of",
"unfolding",
"disasters."
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"Caricature",
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"style",
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"faces",
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"research",
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"methods",
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"The",
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"source",
"domain",
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"texture).",
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"challenge,",
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"caricature",
"shape.",
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"caricatures.",
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[
"We",
"propose",
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"learning,",
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"by",
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"and",
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[
"We",
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"encoders",
"perform",
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"than",
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"CNNs,",
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"and",
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"task.",
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"also",
"find",
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"domain-specific",
"WORD2VEC",
"embeddings",
"outperform",
"generic",
"pre-trained",
"GLOVE",
"embeddings.",
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"features",
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"shape",
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"ELMO",
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"do",
"not",
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"performance.",
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"contradict",
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"or",
"findings",
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"previous",
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"on",
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"element",
"extraction",
"and",
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"labeling",
"tasks,",
"indicating",
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"contract",
"element",
"extraction",
"requires",
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"task-specific",
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"plain",
"TRANSFORMER-based",
"and",
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"BERT",
"#NAME?",
"models,",
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"find",
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[
"Aspect-Based",
"Sentiment",
"Analysis",
"(ABSA)",
"tasks",
"aim",
"to",
"identify",
"consumers'",
"opinions",
"about",
"different",
"aspects",
"of",
"products",
"or",
"services.",
"BERT-based",
"language",
"models",
"have",
"been",
"used",
"successfully",
"in",
"applications",
"that",
"require",
"a",
"deep",
"understanding",
"of",
"the",
"language,",
"such",
"as",
"sentiment",
"analysis.",
"This",
"paper",
"investigates",
"the",
"use",
"of",
"disentangled",
"learning",
"to",
"improve",
"BERT-based",
"textual",
"representations",
"in",
"ABSA",
"tasks.",
"Motivated",
"by",
"the",
"success",
"of",
"disentangled",
"representation",
"learning",
"in",
"the",
"field",
"of",
"computer",
"vision,",
"which",
"aims",
"to",
"obtain",
"explanatory",
"factors",
"of",
"the",
"data",
"representations,",
"we",
"explored",
"the",
"recent",
"DeBERTa",
"model",
"(Decoding-enhanced",
"BERT",
"with",
"Disentangled",
"Attention)",
"to",
"disentangle",
"the",
"syntactic",
"and",
"semantics",
"features",
"from",
"a",
"BERT",
"architecture.",
"Experimental",
"results",
"show",
"that",
"incorporating",
"disentangled",
"attention",
"and",
"a",
"simple",
"fine-tuning",
"strategy",
"for",
"downstream",
"tasks",
"outperforms",
"state-of-the-art",
"models",
"in",
"ABSA's",
"benchmark",
"datasets."
] |
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[
"Classification",
"is",
"an",
"important",
"supervised",
"machine",
"learning",
"method,",
"which",
"isnecessary",
"and",
"challenging",
"issue",
"for",
"ecological",
"research.",
"It",
"offers",
"a",
"way",
"toclassify",
"a",
"dataset",
"into",
"subsets",
"that",
"share",
"common",
"patterns.",
"Notably,",
"there",
"aremany",
"classification",
"algorithms",
"to",
"choose",
"from,",
"each",
"making",
"certain",
"assumptionsabout",
"the",
"data",
"and",
"about",
"how",
"classification",
"should",
"be",
"formed.",
"In",
"this",
"paper,",
"weapplied",
"eight",
"machine",
"learning",
"classification",
"algorithms",
"such",
"as",
"DecisionTrees,",
"Random",
"Forest,",
"Artificial",
"Neural",
"Network,",
"Support",
"Vector",
"Machine,",
"LinearDiscriminant",
"Analysis,",
"k-nearest",
"neighbors,",
"Logistic",
"Regression",
"and",
"Naive",
"Bayeson",
"ecological",
"data.",
"The",
"goal",
"of",
"this",
"study",
"is",
"to",
"compare",
"different",
"machinelearning",
"classification",
"algorithms",
"in",
"ecological",
"dataset.",
"In",
"this",
"analysis",
"wehave",
"checked",
"the",
"accuracy",
"test",
"among",
"the",
"algorithms.",
"In",
"our",
"study",
"we",
"concludethat",
"Linear",
"Discriminant",
"Analysis",
"and",
"k-nearest",
"neighbors",
"are",
"the",
"best",
"methodsamong",
"all",
"other",
"methods"
] |
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[
"In",
"this",
"paper,",
"we",
"propose",
"a",
"novel",
"data",
"augmentation",
"method,",
"referred",
"to",
"as",
"Controllable",
"Rewriting",
"based",
"Question",
"Data",
"Augmentation",
"(CRQDA),",
"for",
"machine",
"reading",
"comprehension",
"(MRC),",
"question",
"generation,",
"and",
"question-answering",
"natural",
"language",
"inference",
"tasks.",
"We",
"treat",
"the",
"question",
"data",
"augmentation",
"task",
"as",
"a",
"constrained",
"question",
"rewriting",
"problem",
"to",
"generate",
"context-relevant,",
"high-quality,",
"and",
"diverse",
"question",
"data",
"samples.",
"CRQDA",
"utilizes",
"a",
"Transformer",
"autoencoder",
"to",
"map",
"the",
"original",
"discrete",
"question",
"into",
"a",
"continuous",
"embedding",
"space.",
"It",
"then",
"uses",
"a",
"pre-trained",
"MRC",
"model",
"to",
"revise",
"the",
"question",
"representation",
"iteratively",
"with",
"gradient-based",
"optimization.",
"Finally,",
"the",
"revised",
"question",
"representations",
"are",
"mapped",
"back",
"into",
"the",
"discrete",
"space,",
"which",
"serve",
"as",
"additional",
"question",
"data.",
"Comprehensive",
"experiments",
"on",
"SQuAD",
"2.0,",
"SQuAD",
"1.1",
"question",
"generation,",
"and",
"QNLI",
"tasks",
"demonstrate",
"the",
"effectiveness",
"of",
"CRQDA"
] |
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[
"Deblurring",
"is",
"the",
"task",
"of",
"restoring",
"a",
"blurred",
"image",
"to",
"a",
"sharp",
"one,",
"retrieving",
"the",
"information",
"lost",
"due",
"to",
"the",
"blur.",
"In",
"blind",
"deblurring",
"we",
"have",
"no",
"information",
"regarding",
"the",
"blur",
"kernel.",
"As",
"deblurring",
"can",
"be",
"considered",
"as",
"an",
"image",
"to",
"image",
"translation",
"task,",
"deep",
"learning",
"based",
"solutions,",
"including",
"the",
"ones",
"which",
"use",
"GAN",
"(Generative",
"Adversarial",
"Network),",
"have",
"been",
"proven",
"effective",
"for",
"deblurring.",
"Most",
"of",
"them",
"have",
"an",
"encoder-decoder",
"structure.",
"Our",
"objective",
"is",
"to",
"try",
"different",
"GAN",
"structures",
"and",
"improve",
"its",
"performance",
"through",
"various",
"modifications",
"to",
"the",
"existing",
"structure",
"for",
"supervised",
"deblurring.",
"In",
"supervised",
"deblurring",
"we",
"have",
"pairs",
"of",
"blurred",
"and",
"their",
"corresponding",
"sharp",
"images,",
"while",
"in",
"the",
"unsupervised",
"case",
"we",
"have",
"a",
"set",
"of",
"blurred",
"and",
"sharp",
"images",
"but",
"their",
"is",
"no",
"correspondence",
"between",
"them.",
"Modifications",
"to",
"the",
"structures",
"is",
"done",
"to",
"improve",
"the",
"global",
"perception",
"of",
"the",
"model.",
"As",
"blur",
"is",
"non-uniform",
"in",
"nature,",
"for",
"deblurring",
"we",
"require",
"global",
"information",
"of",
"the",
"entire",
"image,",
"whereas",
"convolution",
"used",
"in",
"CNN",
"is",
"able",
"to",
"provide",
"only",
"local",
"perception.",
"Deep",
"models",
"can",
"be",
"used",
"to",
"improve",
"global",
"perception",
"but",
"due",
"to",
"large",
"number",
"of",
"parameters",
"it",
"becomes",
"difficult",
"for",
"it",
"to",
"converge",
"and",
"inference",
"time",
"increases,",
"to",
"solve",
"this",
"we",
"propose",
"the",
"use",
"of",
"attention",
"module",
"(non-local",
"block)",
"which",
"was",
"previously",
"used",
"in",
"language",
"translation",
"and",
"other",
"image",
"to",
"image",
"translation",
"tasks",
"in",
"deblurring.",
"Use",
"of",
"residual",
"connection",
"also",
"improves",
"the",
"performance",
"of",
"deblurring",
"as",
"features",
"from",
"the",
"lower",
"layers",
"are",
"added",
"to",
"the",
"upper",
"layers",
"of",
"the",
"model.",
"It",
"has",
"been",
"found",
"that",
"classical",
"losses",
"like",
"L1,",
"L2,",
"and",
"perceptual",
"loss",
"also",
"help",
"in",
"training",
"of",
"GAN",
"s",
"when",
"added",
"together",
"with",
"adversarial",
"loss.",
"We",
"also",
"concatenate",
"edge",
"information",
"of",
"the",
"image",
"to",
"observe",
"its",
"effects",
"on",
"deblurring.",
"We",
"also",
"use",
"feedback",
"modules",
"to",
"retain",
"long",
"term",
"dependencies"
] |
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[
"We",
"propose",
"Unicoder-VL,",
"a",
"universal",
"encoder",
"that",
"aims",
"to",
"learn",
"joint",
"representations",
"of",
"vision",
"and",
"language",
"in",
"a",
"pre-training",
"manner.",
"Borrow",
"ideas",
"from",
"cross-lingual",
"pre-trained",
"models,",
"such",
"as",
"XLM",
"and",
"Unicoder,",
"both",
"visual",
"and",
"linguistic",
"contents",
"are",
"fed",
"into",
"a",
"multi-layer",
"Transformer",
"for",
"the",
"cross-modal",
"pre-training,",
"where",
"three",
"pre-trained",
"tasks",
"are",
"employed,",
"including",
"Masked",
"Language",
"Modeling",
"(MLM),",
"Masked",
"Object",
"Classification",
"(MOC)",
"and",
"Visual-linguistic",
"Matching",
"(VLM).",
"The",
"first",
"two",
"tasks",
"learn",
"context-aware",
"representations",
"for",
"input",
"tokens",
"based",
"on",
"linguistic",
"and",
"visual",
"contents",
"jointly.",
"The",
"last",
"task",
"tries",
"to",
"predict",
"whether",
"an",
"image",
"and",
"a",
"text",
"describe",
"each",
"other.",
"After",
"pretraining",
"on",
"large-scale",
"image-caption",
"pairs,",
"we",
"transfer",
"Unicoder-VL",
"to",
"caption-based",
"image-text",
"retrieval",
"and",
"visual",
"commonsense",
"reasoning,",
"with",
"just",
"one",
"additional",
"output",
"layer.",
"We",
"achieve",
"state-of-the-art",
"or",
"comparable",
"results",
"on",
"both",
"two",
"tasks",
"and",
"show",
"the",
"powerful",
"ability",
"of",
"the",
"cross-modal",
"pre-training."
] |
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[
"This",
"paper",
"describes",
"our",
"system",
"at",
"SemEval",
"2019,",
"Task",
"3",
"(EmoContext),",
"which",
"focused",
"on",
"the",
"contextual",
"detection",
"of",
"emotions",
"in",
"a",
"dataset",
"of",
"3-round",
"dialogues.",
"For",
"our",
"final",
"system,",
"we",
"used",
"a",
"neural",
"network",
"with",
"pretrained",
"ELMo",
"word",
"embeddings",
"and",
"POS",
"tags",
"as",
"input,",
"GRUs",
"as",
"hidden",
"units,",
"an",
"attention",
"mechanism",
"to",
"capture",
"representations",
"of",
"the",
"dialogues,",
"and",
"an",
"SVM",
"classifier",
"which",
"used",
"the",
"learned",
"network",
"representations",
"to",
"perform",
"the",
"task",
"of",
"multi-class",
"classification.This",
"system",
"yielded",
"a",
"micro-averaged",
"F1",
"score",
"of",
"0.7072",
"for",
"the",
"three",
"emotion",
"classes,",
"improving",
"the",
"baseline",
"by",
"approximately",
"12{\\%}."
] |
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6,
6,
6,
6,
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[
"Recognizing",
"shallow",
"linguistic",
"patterns",
",",
"such",
"as",
"basic",
"syntactic",
"relationships",
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"words",
",",
"is",
"a",
"common",
"task",
"in",
"applied",
"natural",
"language",
"and",
"text",
"processing",
".",
"The",
"common",
"practice",
"for",
"approaching",
"this",
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"tedious",
"manual",
"definition",
"of",
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"structures",
",",
"often",
"in",
"the",
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"or",
"finite",
"automata",
".",
"This",
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"memory-based",
"learning",
"method",
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"shallow",
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"text",
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"corpus",
".",
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"data",
"are",
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",",
"in",
"efficient",
"suffix-tree",
"data",
"structures",
".",
"Generalization",
"is",
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"at",
"recognition",
"time",
"by",
"comparing",
"subsequences",
"of",
"the",
"new",
"text",
"to",
"positive",
"and",
"negative",
"evidence",
"in",
"the",
"corpus",
".",
"This",
"way",
",",
"no",
"information",
"in",
"the",
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"is",
"lost",
",",
"as",
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"systems",
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"at",
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".",
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"experimental",
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"phrase",
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"subject-verb",
"and",
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"patterns",
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".",
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"approach",
"enables",
"easy",
"porting",
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"it",
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"patterns",
"for",
"information",
"extraction",
"."
] |
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[
"In",
"the",
"paper,",
"we",
"propose",
"an",
"effective",
"and",
"efficient",
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"Federated",
"Learning",
"(ComFedL)",
"algorithm",
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"a",
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"Learning",
"(FL)",
"framework,",
"which",
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"machine",
"learning",
"problems",
"with",
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"hierarchical",
"structure",
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"distributionally",
"robust",
"federated",
"learning",
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"meta",
"learning",
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").",
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"analysis",
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"some",
"mild",
"conditions,",
"and",
"prove",
"that",
"it",
"achieves",
"a",
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"convergence",
"rate",
"of",
"$O(\\frac{1}{\\sqrt{T}})$,",
"where",
"$T$",
"denotes",
"the",
"number",
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"iteration.",
"To",
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"our",
"knowledge,",
"our",
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"the",
"first",
"work",
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"with",
"composition",
"stochastic",
"optimization.",
"In",
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"optimization",
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"divergence",
"regularization.",
"At",
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"also",
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"optimization",
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[
"There",
"are",
"mainly",
"two",
"types",
"of",
"state-of-the-art",
"object",
"detectors.",
"On",
"one",
"hand,we",
"have",
"two-stage",
"detectors,",
"such",
"as",
"Faster",
"R-CNN",
"(Region-based",
"ConvolutionalNeural",
"Networks)",
"or",
"Mask",
"R-CNN,",
"that",
"(i)",
"use",
"a",
"Region",
"Proposal",
"Network",
"togenerate",
"regions",
"of",
"interests",
"in",
"the",
"first",
"stage",
"and",
"(ii)",
"send",
"the",
"regionproposals",
"down",
"the",
"pipeline",
"for",
"object",
"classification",
"and",
"bounding-boxregression.",
"Such",
"models",
"reach",
"the",
"highest",
"accuracy",
"rates,",
"but",
"are",
"typicallyslower.",
"On",
"the",
"other",
"hand,",
"we",
"have",
"single-stage",
"detectors,",
"such",
"as",
"YOLO",
"(YouOnly",
"Look",
"Once)",
"and",
"SSD",
"(Singe",
"Shot",
"MultiBox",
"Detector),",
"that",
"treat",
"objectdetection",
"as",
"a",
"simple",
"regression",
"problem",
"by",
"taking",
"an",
"input",
"image",
"and",
"learningthe",
"class",
"probabilities",
"and",
"bounding",
"box",
"coordinates.",
"Such",
"models",
"reach",
"loweraccuracy",
"rates,",
"but",
"are",
"much",
"faster",
"than",
"two-stage",
"object",
"detectors.",
"In",
"thispaper,",
"we",
"propose",
"to",
"use",
"an",
"image",
"difficulty",
"predictor",
"to",
"achieve",
"an",
"optimaltrade-off",
"between",
"accuracy",
"and",
"speed",
"in",
"object",
"detection.",
"The",
"image",
"difficultypredictor",
"is",
"applied",
"on",
"the",
"test",
"images",
"to",
"split",
"them",
"into",
"easy",
"versus",
"hardimages.",
"Once",
"separated,",
"the",
"easy",
"images",
"are",
"sent",
"to",
"the",
"faster",
"single-stagedetector,",
"while",
"the",
"hard",
"images",
"are",
"sent",
"to",
"the",
"more",
"accurate",
"two-stagedetector.",
"Our",
"experiments",
"on",
"PASCAL",
"VOC",
"2007",
"show",
"that",
"using",
"image",
"difficultycompares",
"favorably",
"to",
"a",
"random",
"split",
"of",
"the",
"images.",
"Our",
"method",
"is",
"flexible,",
"inthat",
"it",
"allows",
"to",
"choose",
"a",
"desired",
"threshold",
"for",
"splitting",
"the",
"images",
"into",
"easyversus",
"hard."
] |
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[
"In",
"this",
"paper,",
"we",
"propose",
"a",
"broad",
"comparison",
"between",
"Fully",
"Convolutional",
"Networks",
"(FCN",
"s)",
"and",
"Mask",
"Region-based",
"Convolutional",
"Neural",
"Networks",
"(Mask-RCNNs)",
"applied",
"in",
"the",
"Salient",
"Object",
"Detection",
"(SOD)",
"context.",
"Studies",
"in",
"the",
"SOD",
"literature",
"usually",
"explore",
"architectures",
"based",
"in",
"FCN",
"s",
"to",
"detect",
"salient",
"regions",
"and",
"objects",
"in",
"visual",
"scenes.",
"However,",
"besides",
"the",
"promising",
"results",
"achieved,",
"FCN",
"s",
"showed",
"issues",
"in",
"some",
"challenging",
"scenarios.",
"Fairly",
"recently",
"studies",
"in",
"the",
"SOD",
"literature",
"proposed",
"the",
"use",
"of",
"a",
"Mask-RCNN",
"approach",
"to",
"overcome",
"such",
"issues.",
"However,",
"there",
"is",
"no",
"extensive",
"comparison",
"between",
"the",
"two",
"networks",
"in",
"the",
"SOD",
"literature",
"endorsing",
"the",
"effectiveness",
"of",
"Mask-RCNNs",
"over",
"FCN",
"when",
"segmenting",
"salient",
"objects.",
"Aiming",
"to",
"effectively",
"show",
"the",
"superiority",
"of",
"Mask-RCNNs",
"over",
"FCN",
"s",
"in",
"the",
"SOD",
"context,",
"we",
"compare",
"two",
"variations",
"of",
"Mask-RCNNs",
"with",
"two",
"variations",
"of",
"FCN",
"s",
"in",
"eight",
"datasets",
"widely",
"used",
"in",
"the",
"literature",
"and",
"in",
"four",
"metrics.",
"Our",
"findings",
"show",
"that",
"in",
"this",
"context",
"Mask-RCNNs",
"achieved",
"an",
"improvement",
"on",
"the",
"F-measure",
"up",
"to",
"47%",
"over",
"FCN",
"s."
] |
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[
"Streaming",
"adaptations",
"of",
"manifold",
"learning",
"based",
"dimensionality",
"reduction",
"methods,",
"such",
"as",
"Isomap,",
"are",
"based",
"on",
"the",
"assumption",
"that",
"a",
"small",
"initial",
"batch",
"of",
"observations",
"is",
"enough",
"for",
"exact",
"learning",
"of",
"the",
"manifold,",
"while",
"remaining",
"streaming",
"data",
"instances",
"can",
"be",
"cheaply",
"mapped",
"to",
"this",
"manifold.",
"However,",
"there",
"are",
"no",
"theoretical",
"results",
"to",
"show",
"that",
"this",
"core",
"assumption",
"is",
"valid.",
"Moreover,",
"such",
"methods",
"typically",
"assume",
"that",
"the",
"underlying",
"data",
"distribution",
"is",
"stationary.",
"Such",
"methods",
"are",
"not",
"equipped",
"to",
"detect,",
"or",
"handle,",
"sudden",
"changes",
"or",
"gradual",
"drifts",
"in",
"the",
"distribution",
"that",
"may",
"occur",
"when",
"the",
"data",
"is",
"streaming.",
"We",
"present",
"theoretical",
"results",
"to",
"show",
"that",
"the",
"quality",
"of",
"a",
"manifold",
"asymptotically",
"converges",
"as",
"the",
"size",
"of",
"data",
"increases.",
"We",
"then",
"show",
"that",
"a",
"Gaussian",
"Process",
"Regression",
"(GPR",
")",
"model,",
"that",
"uses",
"a",
"manifold-specific",
"kernel",
"function",
"and",
"is",
"trained",
"on",
"an",
"initial",
"batch",
"of",
"sufficient",
"size,",
"can",
"closely",
"approximate",
"the",
"state-of-art",
"streaming",
"Isomap",
"algorithms.",
"The",
"predictive",
"variance",
"obtained",
"from",
"the",
"GPR",
"prediction",
"is",
"then",
"shown",
"to",
"be",
"an",
"effective",
"detector",
"of",
"changes",
"in",
"the",
"underlying",
"data",
"distribution.",
"Results",
"on",
"several",
"synthetic",
"and",
"real",
"data",
"sets",
"show",
"that",
"the",
"resulting",
"algorithm",
"can",
"effectively",
"learn",
"lower",
"dimensional",
"representation",
"of",
"high",
"dimensional",
"data",
"in",
"a",
"streaming",
"setting,",
"while",
"identifying",
"shifts",
"in",
"the",
"generative",
"distribution."
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[
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"results",
"show",
"that",
"deep",
"neural",
"networks",
"using",
"contextual",
"embeddings",
"significantly",
"outperform",
"non-contextual",
"embeddings",
"on",
"a",
"majority",
"of",
"text",
"classification",
"task.",
"We",
"offer",
"precomputed",
"embeddings",
"from",
"popular",
"contextual",
"ELMo",
"model",
"for",
"seven",
"languages:",
"Croatian,",
"Estonian,",
"Finnish,",
"Latvian,",
"Lithuanian,",
"Slovenian,",
"and",
"Swedish.",
"We",
"demonstrate",
"that",
"the",
"quality",
"of",
"embeddings",
"strongly",
"depends",
"on",
"the",
"size",
"of",
"training",
"set",
"and",
"show",
"that",
"existing",
"publicly",
"available",
"ELMo",
"embeddings",
"for",
"listed",
"languages",
"shall",
"be",
"improved.",
"We",
"train",
"new",
"ELMo",
"embeddings",
"on",
"much",
"larger",
"training",
"sets",
"and",
"show",
"their",
"advantage",
"over",
"baseline",
"non-contextual",
"FastText",
"embeddings.",
"In",
"evaluation,",
"we",
"use",
"two",
"benchmarks,",
"the",
"analogy",
"task",
"and",
"the",
"NER",
"task."
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[
"MRI",
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"an",
"inherently",
"slow",
"process,",
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"leads",
"to",
"long",
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"time",
"for",
"high-resolution",
"imaging.",
"The",
"speed",
"of",
"acquisition",
"can",
"be",
"increased",
"by",
"ignoring",
"parts",
"of",
"the",
"data",
"(undersampling).",
"Consequently,",
"this",
"leads",
"to",
"the",
"degradation",
"of",
"image",
"quality,",
"such",
"as",
"loss",
"of",
"resolution",
"or",
"introduction",
"of",
"image",
"artefacts.",
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"work",
"aims",
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"or",
"radial",
"MR",
"acquisitions,",
"with",
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"and",
"with",
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"to",
"no",
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"to",
"conventional",
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"like",
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"sensing.",
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"recent",
"times,",
"deep",
"learning",
"has",
"emerged",
"as",
"a",
"very",
"important",
"area",
"of",
"research",
"and",
"has",
"shown",
"immense",
"potential",
"in",
"solving",
"inverse",
"problems,",
"e.g.",
"MR",
"image",
"reconstruction.",
"In",
"this",
"paper,",
"a",
"deep",
"learning",
"based",
"MR",
"image",
"reconstruction",
"framework",
"is",
"proposed,",
"which",
"includes",
"a",
"modified",
"regularised",
"version",
"of",
"ResNet",
"as",
"the",
"network",
"backbone",
"to",
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"artefacts",
"from",
"the",
"undersampled",
"image,",
"followed",
"by",
"data",
"consistency",
"steps",
"that",
"fusions",
"the",
"network",
"output",
"with",
"the",
"data",
"already",
"available",
"from",
"undersampled",
"k-space",
"in",
"order",
"to",
"further",
"improve",
"reconstruction",
"quality.",
"The",
"performance",
"of",
"this",
"framework",
"for",
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"undersampling",
"patterns",
"has",
"also",
"been",
"tested,",
"and",
"it",
"has",
"been",
"observed",
"that",
"the",
"framework",
"is",
"robust",
"to",
"deal",
"with",
"various",
"sampling",
"patterns,",
"even",
"when",
"mixed",
"together",
"while",
"training,",
"and",
"results",
"in",
"very",
"high",
"quality",
"reconstruction,",
"in",
"terms",
"of",
"high",
"SSIM",
"(highest",
"being",
"0.990$\\pm$0.006",
"for",
"acceleration",
"factor",
"of",
"3.5),",
"while",
"being",
"compared",
"with",
"the",
"fully",
"sampled",
"reconstruction.",
"It",
"has",
"been",
"shown",
"that",
"the",
"proposed",
"framework",
"can",
"successfully",
"reconstruct",
"even",
"for",
"an",
"acceleration",
"factor",
"of",
"20",
"for",
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"(0.968$\\pm$0.005)",
"and",
"17",
"for",
"radially",
"(0.962$\\pm$0.012)",
"sampled",
"data.",
"Furthermore,",
"it",
"has",
"been",
"shown",
"that",
"the",
"framework",
"preserves",
"brain",
"pathology",
"during",
"reconstruction",
"while",
"being",
"trained",
"on",
"healthy",
"subjects."
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[
"Survival",
"outcome",
"prediction",
"is",
"a",
"challenging",
"weakly-supervised",
"and",
"ordinal",
"regression",
"task",
"in",
"computational",
"pathology",
"that",
"involves",
"modeling",
"complex",
"interactions",
"within",
"the",
"tumor",
"microenvironment",
"in",
"gigapixel",
"whole",
"slide",
"images",
"(WSIs).",
"Despite",
"recent",
"progress",
"in",
"formulating",
"WSIs",
"as",
"bags",
"for",
"multiple",
"instance",
"learning",
"(MIL),",
"representation",
"learning",
"of",
"entire",
"WSIs",
"remains",
"an",
"open",
"and",
"challenging",
"problem,",
"especially",
"in",
"overcoming:",
"1)",
"the",
"computational",
"complexity",
"of",
"feature",
"aggregation",
"in",
"large",
"bags,",
"and",
"2)",
"the",
"data",
"heterogeneity",
"gap",
"in",
"incorporating",
"biological",
"priors",
"such",
"as",
"genomic",
"measurements.",
"In",
"this",
"work,",
"we",
"present",
"a",
"Multimodal",
"Co-Attention",
"Transformer",
"(MCAT)",
"framework",
"that",
"learns",
"an",
"interpretable,",
"dense",
"co-attention",
"mapping",
"between",
"WSIs",
"and",
"genomic",
"features",
"formulated",
"in",
"an",
"embedding",
"space.",
"Inspired",
"by",
"approaches",
"in",
"Visual",
"Question",
"Answering",
"(VQA)",
"that",
"can",
"attribute",
"how",
"word",
"embeddings",
"attend",
"to",
"salient",
"objects",
"in",
"an",
"image",
"when",
"answering",
"a",
"question,",
"MCAT",
"learns",
"how",
"histology",
"patches",
"attend",
"to",
"genes",
"when",
"predicting",
"patient",
"survival.",
"In",
"addition",
"to",
"visualizing",
"multimodal",
"interactions,",
"our",
"co-attention",
"transformation",
"also",
"reduces",
"the",
"space",
"complexity",
"of",
"WSI",
"bags,",
"which",
"enables",
"the",
"adaptation",
"of",
"Transformer",
"layers",
"as",
"a",
"general",
"encoder",
"backbone",
"in",
"MIL.",
"We",
"apply",
"our",
"proposed",
"method",
"on",
"five",
"different",
"cancer",
"datasets",
"(4,730",
"WSIs,",
"67",
"million",
"patches).",
"Our",
"experimental",
"results",
"demonstrate",
"that",
"the",
"proposed",
"method",
"consistently",
"achieves",
"superior",
"performance",
"compared",
"to",
"the",
"state-of-the-art",
"methods."
] |
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[
"Model-Agnostic",
"Meta-Learning",
"(MAML",
")",
"has",
"become",
"increasingly",
"popular",
"for",
"training",
"models",
"that",
"can",
"quickly",
"adapt",
"to",
"new",
"tasks",
"via",
"one",
"or",
"few",
"stochastic",
"gradient",
"descent",
"steps.",
"However,",
"the",
"MAML",
"objective",
"is",
"significantly",
"more",
"difficult",
"to",
"optimize",
"compared",
"to",
"standard",
"non-adaptive",
"learning",
"(NAL),",
"and",
"little",
"is",
"understood",
"about",
"how",
"much",
"MAML",
"improves",
"over",
"NAL",
"in",
"terms",
"of",
"the",
"fast",
"adaptability",
"of",
"their",
"solutions",
"in",
"various",
"scenarios.",
"We",
"analytically",
"address",
"this",
"issue",
"in",
"a",
"linear",
"regression",
"setting",
"consisting",
"of",
"a",
"mixture",
"of",
"easy",
"and",
"hard",
"tasks,",
"where",
"hardness",
"is",
"related",
"to",
"the",
"rate",
"that",
"gradient",
"descent",
"converges",
"on",
"the",
"task.",
"Specifically,",
"we",
"prove",
"that",
"in",
"order",
"for",
"MAML",
"to",
"achieve",
"substantial",
"gain",
"over",
"NAL,",
"(i)",
"there",
"must",
"be",
"some",
"discrepancy",
"in",
"hardness",
"among",
"the",
"tasks,",
"and",
"(ii)",
"the",
"optimal",
"solutions",
"of",
"the",
"hard",
"tasks",
"must",
"be",
"closely",
"packed",
"with",
"the",
"center",
"far",
"from",
"the",
"center",
"of",
"the",
"easy",
"tasks",
"optimal",
"solutions.",
"We",
"also",
"give",
"numerical",
"and",
"analytical",
"results",
"suggesting",
"that",
"these",
"insights",
"apply",
"to",
"two-layer",
"neural",
"networks.",
"Finally,",
"we",
"provide",
"few-shot",
"image",
"classification",
"experiments",
"that",
"support",
"our",
"insights",
"for",
"when",
"MAML",
"should",
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"used",
"and",
"emphasize",
"the",
"importance",
"of",
"training",
"MAML",
"on",
"hard",
"tasks",
"in",
"practice."
] |
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6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
6,
7,
6,
6,
6,
6,
6,
6,
6,
6,
6,
7,
6,
6,
6,
6,
6
] |
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