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标签“in”的相关文档，共437条

Understanding Priors in Bayesian Neural Networks at the Unit Level
UnderstandingPriorsinBayesianNeuralNetworksattheUnitLevelMariiaVladimirova12JakobVerbeek1PabloMesejo3JulyanArbel1AbstractworksonBayesianneuralnetworks(Neal,1992;MacKay,1992).Thereisalargevarietyofa...
Neural Networks Bayesian in at
2023-11-13 14:48:54648553.92 KB14
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Understanding and correcting pathologies in the training of learned optimizers
UnderstandingandcorrectingpathologiesinthetrainingoflearnedoptimizersLukeMetz1NiruMaheswaranathan1JeremyNixon1C.DanielFreeman1JaschaSohl-Dickstein1Abstractperparametersearch.Ontheotherhand,acomplem...
and the in Understanding Training
2023-11-13 14:48:5313522.23 MB26
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Understanding and Controlling Memory in Recurrent Neural Networks
UnderstandingandControllingMemoryinRecurrentNeuralNetworksDoronHaviv12AlexnaderRivkind234OmriBarak23Abstract1.introductionTobeeffectiveinsequentialdataprocessing,Re-RecurrentNeuralNetworks(RNN)aret...
Neural and Recurrent in Memory
2023-11-13 14:48:5217521.41 MB13
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Transfer of Samples in Policy Search via Multiple Importance Sampling
TransferofSamplesinPolicySearchviaMultipleImportanceSamplingAndreaTirinzoni1MattiaSalvini1MarcelloRestelli1Abstractagentissupposedtoreuseknowledgeacquiredfromasetofsourcetaskstoacceleratethelearnin...
of via in Policy Transfer
2023-11-13 14:48:51604452.37 KB15
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Traditional and Heavy Tailed Self Regularization in Neural Network Models
TraditionalandHeavyTailedSelfRegularizationinNeuralNetworkModelsCharlesH.Martin1MichaelW.Mahoney2Abstracttheorydidnotapplytothesesystems(Vapniketal.,1994).Itwasoriginallyassumedthatlocalminimainthe...
and in Regularization Self Traditional
2023-11-13 14:48:501787627.98 KB5
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Towards Accurate Model Selection in Deep Unsupervised Domain Adaptation
TowardsAccurateModelSelectioninDeepUnsupervisedDomainAdaptationKaichaoYou12XimeiWang12MingshengLong12MichaelI.Jordan3Abstractnaturalinrecognitiontaskswheredeepmodelshaveshowntheirsuperiority(Longet...
Selection Model Deep Unsupervised in
2023-11-13 14:48:491780512.18 KB10
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Toward Understanding the Importance of Noise in Training Neural Networks
TowardsUnderstandingtheImportanceofNoiseinTrainingNeuralNetworksMoZhou1TianyiLiu2YanLi2DachaoLin1EnluZhou2TuoZhao2AbstractSimpleﬁrstorderalgorithmssuchasStochasticGradientDescent(SGD)anditsvariant...
of the in Importance Toward
2023-11-13 14:48:4816572.01 MB27
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Toward Controlling Discrimination in Online Ad Auctions
TowardControllingDiscriminationinOnlineAdAuctionsL.ElisaCelis1AnayMehrotra2NisheethK.Vishnoi3Abstracttheadvertiserischarged(Muthukrishnan,2009;Yuanetal.,2012;Varian,2007).Asitisnotpracticalforadver...
Online in Toward Discrimination auctions
2023-11-13 14:48:48557546.64 KB23
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Tighter Problem-Dependent Regret Bounds in Reinforcement Learning without Domain Knowledge using Value Function Bounds
TighterProblem-DependentRegretBoundsinReinforcementLearningwithoutDomainKnowledgeusingValueFunctionBoundsAndreaZanette1EmmaBrunskill2AbstractFortunatelyinpracticereinforcementlearningalgorithmsof-t...
Learning Reinforcement in Regret bounds
2023-11-13 14:48:48577493.86 KB20
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The Value Function Polytope in Reinforcement Learning
TheValueFunctionPolytopeinReinforcementLearningRobertDadashi1AdrienAliTa¨ıga12NicolasLeRoux1DaleSchuurmans13MarcG.Bellemare1AbstractLinetheorem.Weshowthatpoliciesthatagreeonallbutonestategenerate...
Learning Reinforcement the in Value
2023-11-13 14:48:466535.41 MB14
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The information-theoretic value of unlabeled data in semi-supervised learning
Theinformation-TheoreticValueofUnlabeledDatainSemi-SupervisedLearningAlexanderGolovnev1Da´vidPa´l2Bala´zsSzo¨re´nyi2Abstractofalgorithmsindexedbythe(uncountablymany)distri-butionsoverthedomain...
of the Data in Value
2023-11-13 14:48:45609376.33 KB20
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The Anisotropic Noise in Stochastic Gradient Descent Its Behavior of Escaping from Sharp Minima and Regularization Effects
TheAnisotropicNoiseinStochasticGradientDescent:ItsBehaviorofEscapingfromSharpMinimaandRegularizationEffectsZhanxingZhu123JingfengWu1BingYu1LeiWu1JinwenMa1Abstract90Understandingthebehaviorofstochas...
Gradient Descent Stochastic the in
2023-11-13 14:48:4412286.72 MB6
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SWALP Stochastic Weight Averaging in Low Precision Training
SWALP:StochasticWeightAveraginginLow-PrecisionTrainingGuandaoYang1TianyiZhang1PolinaKirichenko1JunwenBai1AndrewGordonWilson1ChristopherDeSa1Abstractandaccumulategradientinformationinhigherprecision...
Precision Stochastic in low Weight
2023-11-13 14:48:421126790.03 KB6
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Submodular Streaming in All Its Glory Tight Approximation, Minimum Memory and Low Adaptive Complexity
SubmodularStreaminginAllItsGlory:TightApproximation,MinimumMemoryandLowAdaptiveComplexityEhsanKazemi1MarkoMitrovic1MortezaZadimoghaddam2SilvioLattanzi2AminKarbasi1Abstractnon-negativesetfunctionf:2...
Submodular in Tight All its
2023-11-13 14:48:419321.99 MB17
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Statistics and Samples in Distributional Reinforcement Learning
StatisticsandSamplesinDistributionalReinforcementLearningMarkRowland1RobertDadashi2SaurabhKumar2Re´miMunos1MarcG.Bellemare2WillDabney1AbstractthatDRLalgorithmscanbeviewedascombiningastatisti-cales...
Learning and Reinforcement in Samples
2023-11-13 14:48:3716412.3 MB25
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Static Automatic Batching in TensorFlow
StaticAutomaticBatchinginTensorFlowAshishAgarwal1Abstractterpretedlanguageslikepythoncanmakethisbottleneckworse.Dynamicneuralnetworksarebecomingincreas-inglycommon,andyetitishardtoimplementGiventhe...
Automatic in Static Batching TensorFlow
2023-11-13 14:48:377551.39 MB8
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Self-similar Epochs Value in arrangement
Self-SimilarEpochs:ValueinArrangementEliavBuchnik12EdithCohen21AvinatanHassidim2YossiMatias2Abstractbroad:entitiescanbeofoneormultipletypesandexampleassociationsusedfortrainingcanberaworpreprocesse...
in Value Epochs Self-similar arrangement
2023-11-13 14:48:3112733.33 MB5
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Scalable Learning in Reproducing Kernel Krein Spaces
ScalableLearninginReproducingKernelKre˘ınSpacesDinoOglic1ThomasGärtner2AbstractandSmola,2001).TheNyströmmethod(Nyström,1930;SmolaandSchölkopf,2000;WilliamsandSeeger,2001)isWeprovidetheﬁrstma...
Learning Kernel in Spaces Scalable
2023-11-13 14:48:281784431.79 KB9
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Regularization in directable environments with application to Tetris
RegularizationinDirectableEnvironmentswithApplicationtoTetrisJanMalteLichtenberg1O¨zgu¨rS¸ims¸ek1Abstractonregularization.Speciﬁcally,weproposeamodelthatintroducesabiastowardgivingallfeaturese...
with in to Regularization Application
2023-11-13 14:48:231338420.65 KB28
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Rehashing Kernel Evaluation in High Dimensions
RehashingKernelEvaluationinHighDimensionsParisSiminelakis1KexinRong1PeterBailis1MosesCharikar1PhilipLevis1Abstract(a)kernel(b)difﬁcultcase(c)simplecaseKernelmethodsareeffectivebutdonotscalewellFig...
Kernel in High Dimensions Evaluation
2023-11-13 14:48:2310211.4 MB6
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