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标签“on”的相关文档，共225条

Affine Invariant Analysis of Frank-Wolfe on Strongly Convex Sets
AfﬁneInvariantAnalysisofFrank-WolfeonStronglyConvexSetsThomasKerdreux1LewisLiu23SimonLacosteJulien2345DamienScieur43AbstractAlgorithm1Frank-WolfeAlgorithmLMOLine-searchItisknownthattheFrank-Wolfe(...
of Analysis on Invariant Affine
2023-11-16 18:00:281104545.97 KB21
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Accuracy on the Line on the Strong Correlation Between Out-of-Distribution and In-Distribution Generalization
AccuracyontheLine:ontheStrongCorrelationBetweenOut-of-DistributionandIn-DistributionGeneralizationJohnMiller1RohanTaori2AditiRaghunathan2ShioriSagawa2PangWeiKoh2VaishaalShankar1PercyLiang2YairCarmo...
on the Strong Accuracy between
2023-11-16 18:00:2110042.1 MB22
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A Functional Perspective on Learning Symmetric Functions with Neural Networks
AFunctionalPerspectiveonLearningSymmetricFunctionswithNeuralNetworksAaronZweig1JoanBruna12AbstractSuchsymmetricfunctionsappearnaturallyacrossseveraldomains,includingparticlephysics,computergraphics...
Learning with on Functions Symmetric
2023-11-16 17:52:021476547.22 KB10
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A statistical perspective on distillation
AStatisticalPerspectiveonDistillationAdityaKrishnaMenon1AnkitSinghRawat1SashankJ.Reddi1SeungyeonKim1SanjivKumar1Abstractetal.,2019).onecommonlyacceptedintuitionfromHintonetal.(2015)isthattheteacher...
on Statistical Perspective Distillation
2023-11-16 17:51:5919003.16 MB24
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A Representation Learning Perspective on the Importance of Train-Validation Splitting in Meta-Learning
ARepresentationLearningPerspectiveontheImportanceofTrain-ValidationSplittinginMeta-LearningNikunjSaunshi1ArushiGupta1WeiHu1Abstractfrommany“train”taskstolearnausefulpriorthatcanhelpsolvenew“test...
Learning of on the Representation
2023-11-16 17:51:5713421.28 MB7
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Understanding the Impact of Model Incoherence on Convergence of Incremental SGD with Random Reshuffle
UnderstandingtheImpactofModelIncoherenceonConvergenceofIncrementalSGDwithRandomReshuffeShaocongMa1YiZhou1Abstractthesamplelossofthei-thdatasample.Suchaproblemformulationcoversavarietyofmachinelearn...
of Model on the Understanding
2023-11-14 21:46:557873.24 MB25
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Understanding Contrastive Representation Learning through Geometry on the Hypersphere
UnderstandingContrastiveRepresentationLearningthroughAlignmentandUniformityontheHypersphereTongzhouWang1PhillipIsola1AbstractContrastiverepresentationlearninghasbeenout-Alignment:Similarsampleshave...
Learning on through Geometry Representation
2023-11-14 21:46:548532.39 MB10
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The Effect of Natural Distribution Shift on Question Answering Models
TheEffectofNaturalDistributionShiftonQuestionAnsweringModelsJohnMiller1KarlKrauth1BenjaminRecht1LudwigSchmidt1AbstractmerelytoobtainhighscoresontheSQuADleaderboard,butrathertogeneralizetonewexample...
of on the Natural Distribution
2023-11-14 21:46:421814564.62 KB4
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Tensor denoising and completion based on ordinal observations
TensordenoisingandcompletionbasedonordinalobservationsChanwooLee1MiaoyanWang1Abstracttensor,therebyefﬁcientlyreducingtheintrinsicdimensioninbothproblems.Higher-ordertensorsarisefrequentlyinapplica...
Completion and on Tensor Based
2023-11-14 21:46:4117001 MB6
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Teaching with Limited Information on the Learners Behaviour
TeachingwithLimitedInformationontheLearner’sBehaviourFerdinandoCicalese1SergioFilho2EduardoLaber2MarcoMolinaro2Abstractbeenontheinteractivesetting(Liuetal.,2017;Chenetal.,2018;Liuetal.,2018;Dasgup...
with on the Learners Limited
2023-11-14 21:46:401589365.02 KB19
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Stochastic Flows and Geometric Optimization on the Orthogonal Group
StochasticFlowsandGeometricOptimizationontheOrthogonalGroupKrzysztofChoromanski12DavidCheikhi3JaredDavis1ValeriiLikhosherstov4AchilleNazaret3AchrafBahamou2XingyouSong1MrugankAkarte2JackParker-Holde...
Optimization and on Stochastic the
2023-11-14 21:46:3115992.03 MB17
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on Variational Learning of Controllable Representations for Text without Supervision
onVariationalLearningofControllableRepresentationsforTextwithoutSupervisionPengXu1JackieChiKitCheung123YanshuaiCao1Abstracttexts.Recently,VAEsandotherunsupervisedgenerativemodelshavefoundsuccessesi...
Learning of for Representations Variational
2023-11-14 21:45:36692967.88 KB17
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on Unbalanced Optimal Transport An Analysis of Sinkhorn Algorithm
onUnbalancedOptimalTransport:AnAnalysisofSinkhornAlgorithmKhiemPham1KhangLe1NhatHo2TungPham13HungBui1Abstractogy(Schiebingeretal.,2019),computationalimaging(Leeetal.,2019),deeplearning(Yang&Uhler,2...
of An Analysis on Optimal
2023-11-14 21:45:361263419.94 KB25
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on Thompson Sampling with Langevin Algorithms
onThompsonSamplingwithLangevinAlgorithmsEricMazumdar1AldoPacchiano1Yi-AnMa23PeterL.Bartlett14MichaelI.Jordan14Abstractexploitationtradeoffs(Aueretal.,2002;LattimoreandSzepesva´ri,2020),whereinanal...
Sampling Algorithms with on Langevin
2023-11-14 21:45:361201341.36 KB14
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on Validation and Planning of An Optimal Decision Rule with Application in Healthcare Studies
onValidationandPlanningofAnOptimalDecisionRulewithApplicationinHealthcareStudiesHengruiCai1WenbinLu1RuiSong1Abstractsionforallindividuals.Anumberofmethodshavebeendevelopedforestimatingoptimaldecisi...
of and An on Optimal
2023-11-14 21:45:361326312.33 KB25
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on the Theoretical Properties of the Network Jackknife
ontheTheoreticalPropertiesoftheNetworkJackknifeQiaohuiLin1RobertLunde1PurnamritaSarkar1Abstractetal.,2017;Gonenetal.,2010;Kallaugheretal.,2019).However,comparativelylittleattentionhasbeenpaidtoWest...
of on the Network Theoretical
2023-11-14 21:45:351818616.47 KB4
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on the Unreasonable Effectiveness of the Greedy Algorithm Greedy Adapts to Sharpness
ontheUnreasonableEffectivenessoftheGreedyAlgorithm:GreedyAdaptstoSharpnessSebastianPokutta1MohitSingh2AlfredoTorrico3Abstract(Kempeetal.,2003).Giventheimportanceofsubmodularoptimization,therehasbee...
of Algorithm on the Greedy
2023-11-14 21:45:35734342.96 KB25
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on the Sample Complexity of Adversarial Multi-Source PAC Learning
ontheSampleComplexityofAdversarialMulti-SourcePACLearningNikolaKonstantinov1EliasFrantar12DanAlistarh1ChristophH.Lampert1Abstractetal.,2019).Robustnessattrainingtime,however,isrepre-sentedlesspromi...
of Adversarial Complexity on the
2023-11-14 21:45:351562273.56 KB23
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on the Number of Linear Regions of Convolutional Neural Networks
ontheNumberofLinearRegionsofConvolutionalNeuralNetworksHuanXiong1LeiHuang2MengyangYu2LiLiu2FanZhu2LingShao12AbstractoneexplanationforthesuperiorityofNNsistheirpow-erfulexpressivity,i.e.,theycanrepr...
of on the Convolutional Linear
2023-11-14 21:45:351574321.72 KB6
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on the Power of Compressed Sensing with Generative Models
onthePowerofCompressedSensingwithGenerativeModelsAkshayKamath1SushrutKarmalkar1EricPrice1Abstractofthecompressedrepresentationofxthantoitsambientdimensionn.Thegoalofcompressedsensingistolearnastruc...
of with on the Compressed
2023-11-14 21:45:341687381.33 KB28
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