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标签“the”的相关文档，共346条

What’s in the Box Exploring the Inner Life of Neural Networks with Robust Rules
What’sintheBox?ExploringtheInnerLifeofNeuralNetworkswithRobustRulesJonasFischer1AnnaOla´h1JillesVreeken2AbstractYaretypicallyactivewhenneuronsXare.Forrobustnessweexplicitlyallowfornoise,andtoensu...
the in Exploring Box What
2023-11-16 19:42:2613672.21 MB22
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Variational (Gradient) Estimate of the Score Function in Energy-based Latent Variable Models
Variational(Gradient)EstimateoftheScoreFunctioninEnergy-basedLatentVariableModelsFanBao12KunXu1ChongxuanLi1LanqingHong2JunZhu1BoZhang1Abstractsivepower(Salakhutdinov&Hinton,2009;Baoetal.,2020)andto...
of Variational Gradient the Function
2023-11-16 19:42:2211812.28 MB29
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Understanding the Dynamics of Gradient Flow in Overparameterized Linear models
UnderstandingtheDynamicsofGradientFlowinOverparameterizedLinearModelsSalmaTarmoun12GuilhermeFranc¸a13BenjaminHaeffele14Rene´Vidal14Abstractathoroughanalysisofthedynamicsofoptimizationmeth-ods,suc...
of Gradient the in Understanding
2023-11-16 19:42:181230544.93 KB7
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Uncovering the Connections Between Adversarial Transferability and Knowledge Transferability
UncoveringtheConnectionsBetweenAdversarialTransferabilityandKnowledgeTransferabilityKaizhaoLiang1JackyY.Zhang1BoxinWang1ZhuolinYang1OluwasanmiKoyejo1BoLi1Abstractmulti-lingualmachinetranslation(Don...
Adversarial and the Uncovering between
2023-11-16 19:42:167631.95 MB20
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UCB Momentum Q-learning Correcting the bias without forgetting
UCBMomentumQ-learning:CorrectingthebiaswithoutforgettingPierreMénard1OmarDarwicheDomingues2XuedongShang23MichalValko234Abstractbalancetheexplorationoftheenvironmentandexploitationofthecurrentknowl...
the Momentum without Bias Correcting
2023-11-16 19:42:1513212.56 MB22
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Towards Tight Bounds on the Sample Complexity of Average-reward MDPs
TowardsTightBoundsontheSampleComplexityofAverage-rewardMDPsYujiaJin1AaronSidford1Abstractmakingunderuncertaintyandreinforcementlearning(Puter-man,2014;Sutton&Barto,2018).Itisaprominenttheoret-Wepro...
Complexity on the bounds Sample
2023-11-16 19:42:1215061.88 MB3
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Towards the Unification and Robustness of Perturbation and Gradient Based Explanations
TowardstheUniﬁcationandRobustnessofPerturbationandGradientBasedExplanationsSushantAgarwal1ShahinJabbari2ChiragAgarwal2SohiniUpadhyay2ZhiweiStevenWu3HimabinduLakkaraju2Abstractcanunderstandandconse...
of and the Robustness Towards
2023-11-16 19:42:118431.4 MB13
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Toward Understanding the Feature Learning Process of Self-supervised Contrastive Learning
TowardUnderstandingtheFeatureLearningProcessofSelf-supervisedContrastiveLearningZixinWen1YuanzhiLi2Abstractcanevenoutperformthoselearnedbysupervisedlearninginseveraldownstreamtasks.theremakablepote...
Learning of Feature Process the
2023-11-16 19:42:0911322.88 MB3
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Tilting the playing field Dynamical loss functions for machine learning
Tiltingtheplayingﬁeld:DynamicallossfunctionsformachinelearningMiguelRuiz-Garcia12GeZhang1SamuelS.Schoenholz3AndreaJ.Liu1Abstracttionscale(Glorot&Bengio,2010;Xiaoetal.,2018)orlearningrateschedule(H...
the Functions Loss Dynamical Field
2023-11-16 19:42:0811171.23 MB21
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Tighter Bounds on the Log Marginal Likelihood of Gaussian Process Regression Using Conjugate Gradients
TighterBoundsontheLogMarginalLikelihoodofGaussianProcessRegressionusingConjugateGradientsArtemArtemev12DavidR.Burt3MarkvanderWilk1Abstractdientbasedmethodsinordertoautomaticallyselectmodelhyperpara...
on the bounds Likelihood Marginal
2023-11-16 19:42:081193750.65 KB16
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Tightening the Dependence on Horizon in the Sample Complexity of Q-Learning
TighteningtheDependenceonHorizonintheSampleComplexityofQ-LearningGenLi1ChangxiaoCai2YuxinChen2YuantaoGu1YutingWei3YuejieChi4AbstractQ-learning(Borkar&Meyn,2000;Jaakkolaetal.,1994;Szepesva´ri,1998;...
on the in Sample Dependence
2023-11-16 19:42:081037390.16 KB21
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Tight Bounds on the Smallest Eigenvalue of the Neural Tangent Kernel for Deep ReLU Networks
TightBoundsontheSmallestEigenvalueoftheNeuralTangentKernelforDeepReLUNetworksQuynhNguyen1MarcoMondelli2GuidoMontufar13AbstractWeassumethatthenetworkhasasingleoutput,namelynL=1andWL∈RnL−1.Forconsi...
of on the bounds Tight
2023-11-16 19:42:071629577.47 KB22
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the Symmetry between Arms and Knapsacks A Primal-Dual Approach for Bandits with Knapsacks
theSymmetrybetweenArmsandKnapsacks:APrimal-DualApproachforBanditswithKnapsacksXiaochengLi1ChunlinSun2YinyuYe2Abstractmarkproblemfordecisionmakingunderuncertaintythathasbeenstudiedfornearlyacentury....
and the Primal-Dual Symmetry between
2023-11-16 19:42:072000371.89 KB9
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the Power of Adaptivity for Stochastic Submodular Cover
thePowerofAdaptivityforStochasticSubmodularCoverRohanGhuge1AnupamGupta2ViswanathNagarajan1Abstractsoleimanetal.,2015;Batenietal.,2018):herearetwoexamplesfromsensordeploymentandmedicaldiagnosis.Inth...
of for Submodular Stochastic the
2023-11-16 19:42:066232.32 MB10
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the Logical Options Framework
theLogicalOptionsFrameworkBrandonAraki1XiaoLi1KiranVodrahalli2JonathanDeCastro3J.MicahFry4DanielaRus1Abstractingandoptimal,butnotcomposable;theoptionsframework(Suttonetal.,1999)iscomposableandhiera...
the Framework Options logical
2023-11-16 19:42:065911.39 MB10
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the Power of Log-Sum-Exp Sequential Density Ratio Matrix Estimation for Speed-Accuracy Optimization
thePowerofLog-Sum-Exp:SequentialDensityRatioMatrixEstimationforSpeed-AccuracyOptimizationTaikiMiyagawa1AkinoriF.Ebihara1AbstractMorietal.,2018).Earlyclassiﬁcationoftimeseriesisamulti-objectiveopti...
of the Density Sequential Power
2023-11-16 19:42:066591.71 MB25
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the Lipschitz Constant of Self-Attention
theLipschitzConstantofSelf-AttentionHyunjikKim1GeorgePapamakarios1AndriyMnih1Abstractconstraintforneuralnetworks,tocontrolhowmuchanet-work’soutputcanchangerelativetoitsinput.SuchLips-Lipschitzcons...
of the Lipschitz Self-Attention Constant
2023-11-16 19:42:06559498.83 KB23
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the Limits of Min-Max Optimization Algorithms Convergence to Spurious Non-Critical Sets
theLimitsofMin-MaxOptimizationAlgorithms:ConvergencetoSpuriousNon-CriticalSetsYa-PingHsieh1PanayotisMertikopoulos23VolkanCevher4AbstractGivenanalgorithmforsolving(SP),itisthennaturaltoComparedtoord...
of Optimization Algorithms Convergence the
2023-11-16 19:42:068093.08 MB2
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the Implicit Bias for Adaptive Optimization Algorithms on Homogeneous Neural Networks
theImplicitRegularizationforAdaptiveOptimizationAlgorithmsonHomogeneousNeuralNetworksBohanWang1QiMeng1WeiChen1Tie-YanLiu1Abstractprocessing(Youngetal.,2018).Inpractice,deepneuralnetworks(DNN)learne...
Adaptive for Optimization Algorithms the
2023-11-16 19:42:051102737 KB22
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the Heavy-Tail Phenomenon in SGD
theHeavy-TailPhenomenoninSGDMertGürbüzbalaban1UmutS¸ims¸ekli2LingjiongZhu3Abstract1.IntroductionInrecentyears,variousnotionsofcapacityandthelearningprobleminneuralnetworkscanbeexpressedascomple...
the in SGD Heavy-Tail Phenomenon
2023-11-16 19:42:0513331.34 MB2
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