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标签“for”的相关文档，共1143条

What Makes for End-to-End Object Detection
WhatMakesforEnd-to-EndObjectDetection?PeizeSun1YiJiang2EnzeXie1WenqiShao3ZehuanYuan2ChanghuWang2PingLuo1AbstractFigure1.End-to-endobjectdetection.Non-end-to-endobjectdetectorsrequireNMStoremoveredu...
for Detection End-to-End Object What
2023-11-16 19:42:269502.64 MB15
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Weight-covariance alignment for adversarially robust neural networks
Weight-CovarianceAlignmentforAdversariallyRobustNeuralNetworksPanagiotisEustratiadis1HenryGouk1DaLi12TimothyHospedales12Abstract2013).Inordertotacklethisproblem,manyadversarialdefensealgorithmshave...
Neural for Networks Robust Adversarially
2023-11-16 19:42:257483.39 MB30
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Voice2Series Reprogramming Acoustic Models for Time Series Classification
Voice2Series:ReprogrammingAcousticModelsforTimeSeriesClassiﬁcationChao-HanHuckYang1Yun-YunTsai2Pin-YuChen3AbstracttargetreprogrammedsourceoutputtargetoutputLearningtoclassifytimeserieswithlimitedd...
for Models Time Series Reprogramming
2023-11-16 19:42:2417481.51 MB30
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Wasserstein Distributional Normalization for Robust Distributional Certification of Noisy Labeled Data
WassersteinDistributionalNormalizationforRobustDistributionalCertiﬁcationofNoisyLabeledDataSungWooPark1JunseokKwon1AbstractWhilethereareseveralmethodsthatcandealwithnoisy-labeleddata,recentmethods...
of for Robust Wasserstein Distributional
2023-11-16 19:42:241557540.49 KB29
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Vector Quantized Models for Planning
VectorQuantizedModelsforPlanningSherjilOzair12YazheLi1AliRazavi1IoannisAntonoglou1AäronvandenOord1OriolVinyals1AbstractDota2(OpenAIetal.,2019)andStarCraftII(Vinyalsetal.,2019),orrobotics(OpenAIeta...
for Models Vector Planning Quantized
2023-11-16 19:42:238764.98 MB22
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Variational Empowerment as Representation Learning for Goal-Conditioned Reinforcement Learning
VariationalEmpowermentasRepresentationLearningforGoal-BasedReinforcementLearningJongwookChoi†1ArchitSharma†2HonglakLee13SergeyLevine45ShixiangShaneGu4Abstract1IntroductionLearningtoreachgoalstate...
Learning for Variational Representation as
2023-11-16 19:42:2318914.59 MB18
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Variational Auto-Regressive Gaussian Processes for Continual Learning
VariationalAuto-RegressiveGaussianProcessesforContinualLearningSanyamKapoor1TheofanisKaraletsos2ThangD.Bui3Abstract(a)VAR-GP(ours)Throughsequentialconstructionofposteriorson(b)VCL(withcoresetsize10...
Learning for Variational Gaussian Processes
2023-11-16 19:42:229441.67 MB4
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Variance Reduced Training with Stratified Sampling for forecasting Models
VarianceReducedTrainingwithStratiﬁedSamplingforforecastingModelsYuchengLu12YoungsukPark2LifanChen2YuyangWang2ChristopherDeSa1DeanFoster34Abstract2004)arethefolkloremethodsformodelingthedynamicsofa...
for Sampling with Variance Reduced
2023-11-16 19:42:22587695.21 KB29
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Unsupervised Learning of Visual 3D Keypoints for Control
UnsupervisedLearningofVisual3DKeypointsforControlBoyuanChen1PieterAbbeel1DeepakPathak2AbstractFigure1.Weproposeanend-to-endframeworkforunsupervisedlearningof3Dkeypointsfrommulti-viewimages.Thesekey...
3D Learning of for Unsupervised
2023-11-16 19:42:208233.34 MB20
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UneVEn Universal Value Exploration for Multi-Agent Reinforcement Learning
UneVEn:UniversalValueExplorationforMulti-AgentReinforcementLearningTarunGupta1AnujMahajan1BeiPeng1WendelinBo¨hmer2ShimonWhiteson1Abstractfactorization,thejointactionvaluefunctioncanbedecen-trallym...
for Reinforcement Multi-Agent Exploration Value
2023-11-16 19:42:1812832.84 MB30
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UnICORNN A recurrent model for learning very long time dependencies
UnICORNN:ArecurrentmodelforlearningverylongtimedependenciesT.KonstantinRusch1SiddharthaMishra1AbstractsuchasinLSTMs(Hochreiter&Schmidhuber,1997)andGRUs(Choetal.,2014),wheretheadditivestructureofThe...
Learning for Model Recurrent Long
2023-11-16 19:42:18578506.42 KB18
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Uncertainty Weighted Actor-Critic for Offline Reinforcement Learning
UncertaintyWeightedActor-CriticforOfﬂineReinforcementLearningYueWu12ShuangfeiZhai1NitishSrivastava1JoshuaSusskind1JianZhang1RuslanSalakhutdinov2HanlinGoh1Abstractleveragingpriorexperience(Langeeta...
Learning for Reinforcement Uncertainty Actor-Critic
2023-11-16 19:42:1713498.62 MB14
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Trees with Attention for Set Prediction Tasks
TreeswithAttentionforSetPredictionTasksRoyHirsch1RanGilad-Bachrach2AbstractTree-basedmodels,suchasDecisionTree(DT),Randomforest(RF)andGradientBoostingDecisionTree(GBT)Inmanymachinelearningapplicati...
for with Trees Prediction Set
2023-11-16 19:42:1410171.58 MB11
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Trajectory Diversity for Zero-Shot Coordination
TrajectoryDiversityforZero-ShotCoordinationAndreiLupu1BrandonCui2HengyuanHu2JakobFoerster2AbstractFigure1:Thecorridorcoordinationtaskadmitsthreeopti-malSPpolicies,onlyoneofwhichissuitableforZSC.Wes...
for Zero-Shot Trajectory Coordination Diversity
2023-11-16 19:42:148412.02 MB18
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Training Data Subset Selection for Regression with Controlled Generalization Error
TrainingDataSubsetSelectionforRegressionWithControlledGeneralizationErrorDurgaSivasubramanian1RishabhIyer2GaneshRamakrishnan1AbirDe1Abstractreliabilityofthelearnedmodel.Therefore,thesuccessofsevera...
for Selection with Regression Data
2023-11-16 19:42:131657615.54 KB12
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Towards Practical Mean Bounds for Small Samples
TowardsPracticalMeanBoundsforSmallSamplesMyPhan1PhilipS.Thomas1ErikLearned-Miller1Abstractrefertotwoseparatesettings,theone-endedsupportsetting,inwhichthedistributionisknowntofallintheintervalHisto...
for Mean bounds Samples Practical
2023-11-16 19:42:1113021.26 MB13
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Theory of Spectral Method for Union of Subspaces-Based Random Geometry Graph
TheoryofSpectralMethodforUnionofSubspaces-BasedRandomGeometryGraphGenLi1YuantaoGu1AbstracttaskinprocessingdatapointsinUoSistoclusterthesedatapoints,whichisknownasSubspaceClustering(SC).Appli-Spectr...
of for Spectral Theory Method
2023-11-16 19:42:071704325.71 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 19:42:066222.32 MB10
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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 Earth Mover’s Pinball Loss Quantiles for Histogram-Valued Regression
TheEarthMover’sPinballLoss:QuantilesforHistogram-ValuedRegressionFlorianList1AbstractFigure1.ComicofourmethodforDeepLearning-basedhistogramregression:aneuralnetwork(NN)fθwithweightsθistrainedAlt...
for the Loss Earth Mover
2023-11-16 19:42:0510133.09 MB4
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