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标签“of”的相关文档，共557条

On the Generalization Benefit of Noise in Stochastic Gradient Descent
OntheGeneralizationBeneﬁtofNoiseinStochasticGradientDescentSamuelL.Smith1ErichElsen1SohamDe1Abstractbatches,orbecauseauthorsoftencomparedifferentbatchsizesunderaconstantepochbudget(suchthatsmallba...
of on the in generalization
2023-11-14 21:45:32614980.67 KB1
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On the Convergence of Nesterovs Accelerated Gradient Method in Stochastic Settings
OntheConvergenceofNesterov’sAcceleratedGradientMethodinStochasticSettingsMahmoudAssran123MichaelRabbat23AbstractHowever,thetheoreticalunderstandingofacceleratedmeth-odsremainslimitedwhenusedwithst...
of Gradient on Convergence the
2023-11-14 21:45:326948.58 MB11
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On the Expressivity of Neural Networks for Deep Reinforcement Learning
OntheExpressivityofNeuralNetworksforDeepReinforcementLearningKefanDong1YupingLuo2TianheYu3ChelseaFinn3TengyuMa3Abstractwiththeestimateddynamics(Nagabandietal.,2018;Chuaetal.,2018;Wang&Ba,2019).Weco...
of Neural for Networks on
2023-11-14 21:45:3210781012.91 KB29
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On the consistency of top-k surrogate losses
OntheConsistencyofTop-kSurrogateLossesForestYang12SanmiKoyejo13Abstractasampleand/orwhenasamplemaycorrespondtomultiplelabels,e.g.,whenanimageofaparkcontainingapondmayThetop-kerrorisoftenemployedtoe...
of on the Consistency Losses
2023-11-14 21:45:321908343.21 KB28
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On the (In)tractability of Computing Normalizing Constants for the Product of Determinantal Point Processes
Onthe(In)tractabilityofComputingNormalizingConstantsfortheProductofDeterminantalPointProcessesNaotoOhsaka1TatsuyaMatsuoka1Abstractdet(AS,S).Considerasubsetselectiontask:givennitems(e.g.,images(Kule...
of on the in Normalizing
2023-11-14 21:45:31797498.7 KB20
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On Lp-norm Robustness of Ensemble Decision Stumps and Trees
Onp-normRobustnessofEnsembleDecisionStumpsandTreesYihanWang1HuanZhang2HonggeChen3DuaneBoning3Cho-JuiHsieh2Abstractetal.,2017;Ilyasetal.,2018;Brendeletal.,2018;Chengetal.,2019a;2020),variousalgorith...
of on Decision Robustness Ensemble
2023-11-14 21:45:301145526.4 KB7
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On Learning Sets of Symmetric Elements
OnLearningSetsofSymmetricElementsHaggaiMaron1OrLitany2GalChechik31EthanFetaya3Abstracte.g.(Zaheeretal.,2017;Qietal.,2017),havebecometheleadingapproachforsolvingsuchtasks.However,inmanyLearningfromu...
Learning of on Symmetric Sets
2023-11-14 21:45:308023.58 MB24
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On Efficient Constructions of Checkpoints
OnEfﬁcientConstructionsofCheckpointsYuChen1ZhenmingLiu1BinRen1XinJin2AbstractProducingcheckpointsfrequentlyenablesfailedtrainingprocesstorestartwithminimumwastedtime,andservesEfﬁcientconstruction...
of Efficient on Constructions Checkpoints
2023-11-14 21:45:295408.58 MB12
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Nested Subspace Arrangement for Representation of Relational Data
NestedSubspaceArrangementforRepresentationofRelationalDataNozomiHata1ShizuoKaji2AkihiroYoshida1KatsukiFujisawa2Abstracttion,multiplication,differentiation,metric,andtopologysothatvariousoperations,...
of for Subspace Relational Representation
2023-11-14 21:45:2015813.58 MB18
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My Fair Bandit Distributed Learning of Max-Min Fairness with Multi-player Bandits
MyFairBandit:DistributedLearningofMax-MinFairnesswithMulti-playerBanditsIlaiBistritz1TavorZ.Baharav1AmirLeshem2NicholasBambos1Abstracttheenvironment.Isthereanalternativethatliesinthegapbetweenthetw...
Learning of Distributed Bandit Fair
2023-11-14 21:45:1711141.58 MB12
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Model-Agnostic Characterization of Fairness Trade-offs
FACT:ADiagnosticforGroupFairnessTrade-offsJoonSikKim12JiahaoChen3AmeetTalwalkar14Abstractfairness,whichmeasureshowagroupofindividualswithcertainprotectedattributesaretreateddifferentlyfromotherGrou...
of Fairness Model-Agnostic Characterization trade-offs
2023-11-14 21:45:1216421.79 MB6
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Measuring Non-Expert Comprehension of Machine Learning Fairness Metrics
MeasuringNon-ExpertComprehensionofMachineLearningFairnessMetricsDebjaniSaha1CandiceSchumann1DuncanC.McElfresh1JohnP.Dickerson1MichelleL.Mazurek1MichaelCarlTschantz2Abstractoffairnesscanhavesigniﬁc...
Learning of Machine Fairness Measuring
2023-11-14 21:45:081441426.82 KB6
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Low-loss connection of weight vectors distribution-based approaches
Low-lossconnectionofweightvectors:distribution-basedapproachesIvanAnokhin1DmitryYarotsky1AbstractRecentresearchprovidessomefurtherevidenceinfavorofthe“connectedsublevelset”scenario.Aparticulareas...
of Approaches Weight Connection Low-loss
2023-11-14 21:45:0610712.32 MB11
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Linear Convergence of Randomized Primal-Dual Coordinate Method for Large-scale Linear Constrained Convex Programming
LinearConvergenceofRandomizedPrimal-DualCoordinateMethodforLarge-scaleLinearConstrainedConvexProgrammingDaoliZhu1LeiZhao2Abstractadditivewithrespecttothefollowingspacedecomposition,Linearconstraine...
of Coordinate Convergence Method Primal-Dual
2023-11-14 21:45:031680870.33 KB2
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Linear Lower Bounds and Conditioning of Differentiable Games
LinearLowerBoundsandConditioningofDifferentiableGamesAdamIbrahim1WaïssAzizian2GauthierGidel1IoannisMitliagkas1Abstractmind(Meschederetal.,2017),andtomakemattersworse,havebeenoftentunedsuboptimally...
of and Differentiable bounds Linear
2023-11-14 21:45:021164354.95 KB12
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LEEP A New Measure to Evaluate Transferability of Learned Representations
LEEP:ANewMeasuretoEvaluateTransferabilityofLearnedRepresentationsCuongV.Nguyen1TalHassner2MatthiasSeeger1CedricArchambeau1Abstractchoosegoodsourcemodelsforagiventargettask(Achilleetal.,2019;Baoetal...
of to Evaluate New Transferability
2023-11-14 21:45:011491874.69 KB24
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Learning the Valuations of a $k$-demand Agent
LearningtheValuationsofak-demandAgentHanruiZhang1VincentConitzer1AbstractInothercontexts,suchastheallocationofgoods(orbads,e.g.,tasks),agentsareoftenabletomakepayments(orWestudyproblemswherealearne...
Learning of the Agent Valuations
2023-11-14 21:44:571314701.35 KB19
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Learning Task-Agnostic Embedding of Multiple Black-Box Experts for Multi-Task Model Fusion
LearningTask-AgnosticEmbeddingofMultipleBlack-BoxExpertsforMulti-TaskModelFusionTrongNghiaHoang1ChiThanhLam2BryanKianHsiangLow2PatrickJaillet3Abstractwouldthereforehavedifferentdistributionsorstati...
Learning of Multiple Experts Black-box
2023-11-14 21:44:579212.14 MB20
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Learning the piece-wise constant graph structure of a varying Ising model
Learningthepiece-wiseconstantgraphstructureofavaryingIsingmodelBatisteLeBars1PierreHumbert1ArgyrisKalogeratos1NicolasVayatis1Abstractedgebetweentwonodesinthisgraphindicatesthecondi-tionaldependency...
Learning of Graph the Structure
2023-11-14 21:44:566311014.96 KB13
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Learning Mixtures of Graphs from Epidemic Cascades
LearningMixturesofGraphsfromEpidemicCascadesJessicaHoffmann1SoumyaBasu1SurbhiGoel1ConstantineCaramanis1AbstractRodriguezetal.,2013;Chengetal.,2014;Zhaoetal.,2015;Liuetal.,2019),detectingthem(Arias-...
Learning of from graphs Mixtures
2023-11-14 21:44:541644363.94 KB8
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