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标签“by”的相关文档，共69条

Manifold Mixup Better Representations by Interpolating Hidden States
ManifoldMixup:BetterRepresentationsbyInterpolatingHiddenStatesVikasVerma12AlexLamb2ChristopherBeckham2AmirNajaﬁ3IoannisMitliagkas2DavidLopez-Paz4YoshuaBengio2AbstractThisisaworryingprospect,sinced...
Representations Hidden by Better Manifold
2023-11-13 14:47:491385829.77 KB24
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Learning Distance for Sequences by Learning a Ground Metric
LearningDistanceforSequencesbyLearningaGroundMetricBingSu1YingWu2AbstractAlthoughmetriclearninghasachievedaconsiderablematu-ritylevelbothinpracticeandintheory(Belletetal.,2013),Learningdistancestha...
Learning for by Metric Distance
2023-11-13 14:47:37516122.54 KB17
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Improving Model Selection by Employing the Test Data
ImprovingModelSelectionbyEmployingtheTestDataMaxWestphal1WernerBrannath1AbstractThisisinparticulartruewhenlabelleddataisexpensivetoacquireanddatasetsarethusonlyofmodestsizeortheem-Modelselectionand...
Selection Test Model by the
2023-11-13 14:47:301665812.95 KB22
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Flexibly Fair Representation Learning by Disentanglement
FlexiblyFairRepresentationLearningbyDisentanglementElliotCreager12DavidMadras12Jo¨rn-HenrikJacobsen2MarissaA.Weis23KevinSwersky4ToniannPitassi12RichardZemel12AbstractCurrentapproachestofairreprese...
Learning by Representation Fair Disentanglement
2023-11-13 14:47:1411291.21 MB19
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Efficient Training of BERT by Progressively Stacking
EfﬁcientTrainingofBERTbyProgressivelyStackingLinyuanGong1DiHe1ZhuohanLi1TaoQin2LiweiWang13Tie-YanLiu2Abstractespeciallyindomainsthatrequireparticularexpertise.Unsupervisedpre-trainingiscommonlyuse...
of Efficient by Training BERT
2023-11-13 14:47:0212201.61 MB22
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Discovering Options for Exploration by Minimizing Cover Time
DiscoveringOptionsforExplorationbyMinimizingCoverTimeYuuJinnai1JeeWonPark1DavidAbel1GeorgeKonidaris1Abstractoptionsguaranteedtoreducetheexpectedcovertimeusingthetransitionfunctioneithergiventoorlea...
for by Cover Exploration Discovering
2023-11-13 14:46:5516063.97 MB10
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Curiosity-Bottleneck Exploration by Distilling Task-Specific Novelty
Curiosity-Bottleneck:ExplorationbyDistillingTask-SpeciﬁcNoveltyYoungjinKim12WontaeNam∗3HyunwooKim∗2Ji-HoonKim4GunheeKim2Abstractcontainsnovelbuttask-irrelevantinformation1.Forexam-ple,supposearo...
by Exploration Curiosity-Bottleneck Distilling Task-Specific
2023-11-13 14:46:4711882.47 MB11
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Conditioning by adaptive sampling for robust design
ConditioningbyadaptivesamplingforrobustdesignDavidH.Brookes1HahnbeomPark23JenniferListgarten4AbstractAdvancesinbiotechnology,chemistryandmachinelearningallowforthepossibilitytoimprovesuchdesigncycl...
Adaptive for Sampling by Robust
2023-11-13 14:46:4418202.48 MB12
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Breaking Inter-Layer Co-Adaptation by Classifier Anonymization
BreakingInter-LayerCo-AdaptationbyClassiﬁerAnonymizationIkuroSato1KohtaIshikawa1GuoqingLiu1MasayukiTanaka2Abstract0.431.18Thisstudyaddressesanissueofco-adaptation26betweenafeatureextractorandaclas...
by Breaking Classifier Inter-Layer Co-Adaptation
2023-11-13 14:46:3419779.57 MB13
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Acceleration of SVRG and Katyusha X by Inexact Preconditioning
AccelerationofSVRGandKatyushaXbyInexactPreconditioningYanliLiu1FeiFeng1WotaoYin1Abstractregularizerψ(x)isproper,closed,andconvex,butmaybenonsmooth.Anonzeroψ(x)isdesirableinmanyapplica-Empiricalri...
of and by Acceleration Inexact
2023-11-13 14:46:169581.03 MB18
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Non-linear motor control by local learning in spiking neural networks
Non-LinearMotorControlbyLocalLearninginSpikingNeuralNetworksAdityaGilra12WulframGerstner1AbstractDadarlatetal.,2015).Forwardmodelsuseneuralmotorcommandstopredictbodymovement,whileinversemod-Learnin...
Learning by Local in Control
2023-11-13 12:00:16835853.51 KB7
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Network Global Testing by Counting Graphlets
NetworkGlobalTestingbyCountingGraphletsJiashunJin1ZhengTracyKe2ShengmingLuo1AbstractForeachnode,weassignaProbabilityMassFunctionConsideralargesocialnetworkwithpossi-(PMF)πi=(πi(1),πi(2),···,...
by Network Global Testing Counting
2023-11-13 12:00:14654460.49 KB14
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Meta-Learning by Adjusting Priors Based on Extended PAC-Bayes Theory
Meta-LearningbyAdjustingPriorsBasedonExtendedPAC-BayesTheoryRonAmit1RonMeir1Abstractconstraints,e.g.,convolutionsandweightsharing(LeCunetal.,2015).However,oftentherelevantpriorinformationInmeta-lea...
by on Based Meta-Learning Priors
2023-11-13 12:00:1010452.51 MB14
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Learning by Playing Solving Sparse Reward Tasks from Scratch
LearningbyPlaying–SolvingSparseRewardTasksfromScratchMartinRiedmiller1RolandHafner1ThomasLampe1MichaelNeunert1JonasDegrave1TomVandeWiele1VolodymyrMnih1NicolasHeess1TobiasSpringenberg1Abstractsimul...
Learning Sparse by Tasks Playing
2023-11-13 11:59:5419316.45 MB16
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Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam
FastandScalableBayesianDeepLearningbyWeight-PerturbationinAdamMohammadEmtiyazKhan1DidrikNielsen1VootTangkaratt1WuLin2YarinGal3AkashSrivastava4AbstractusingBayes’rule.Unfortunately,thisisinfeasible...
Learning and by Deep Bayesian
2023-11-13 11:59:331733950.24 KB9
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Disentangling by Factorising
DisentanglingbyFactorisingHyunjikKim12AndriyMnih1AbstractVAEWedeﬁneandaddresstheproblemofunsuper-randomlypermute-Discriminatorvisedlearningofdisentangledrepresentationsoneachdimensiondatagenerated...
by Disentangling Factorising
2023-11-13 11:59:295993.47 MB14
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Curriculum Learning by Transfer Learning Theory and Experiments with Deep Networks
CurriculumLearningbyTransferLearning:TheoryandExperimentswithDeepNetworksDaphnaWeinshall1GadCohen1DanAmir1Abstractforcementlearning(e.g.Gravesetal.,2017).Althoughitremainedforthemostpartinthefringe...
Learning and by Curriculum Transfer
2023-11-13 11:59:211532513.52 KB10
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Computational Optimal Transport Complexity by Accelerated Gradient Descent Is Better Than by Sinkhorn’s Algorithm
ComputationalOptimalTransport:ComplexitybyAcceleratedGradientDescentIsBetterThanbySinkhorn’sAlgorithmPavelDvurechensky1AlexanderGasnikov234AlexeyKroshnin234Abstractclustering(Hoetal.,2017),textcla...
Complexity Gradient by Optimal Transport
2023-11-13 11:59:171326412.46 KB4
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Unsupervised Learning by Predicting Noise
UnsupervisedLearningbyPredictingNoisePiotrBojanowski1ArmandJoulin1Abstractlearntheunderlyingdistributionofimages(Vincentetal.,2010;Goodfellowetal.,2014).Whilesomeoftheseap-Convolutionalneuralnetwor...
Learning by Unsupervised Predicting Noise
2023-11-12 20:45:2817412.18 MB26
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Scaling Up Sparse Support Vector Machines by Simultaneous Feature and Sample Reduction
ScalingUpSparseSupportVectorMachinesbySimultaneousFeatureandSampleReductionWeizhongZhang12BinHong13WeiLiu2JiepingYe3DengCai1XiaofeiHe1JieWang3Abstracttionandvariableselectionby1-normpenalty.Thelast...
Sparse by Vector Support Machines
2023-11-12 20:45:12715559.12 KB28
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