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标签“in”的相关文档，共437条

Reinforcement Learning in Configurable Continuous Environments
ReinforcementLearninginConﬁgurableContinuousEnvironmentsAlbertoMariaMetelli1EmanueleGhelﬁ1MarcelloRestelli1AbstractasaConﬁgurableMarkovDecisionProcess(Conf-MDP,Metellietal.,2018).Asintraditional...
Learning Reinforcement in Continuous Configurable
2023-11-13 14:48:231562840.93 KB21
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Recurrent Kalman Networks Factorized inference in High-Dimensional Deep Feature Spaces
RecurrentKalmanNetworks:FactorizedinferenceinHigh-DimensionalDeepFeatureSpacesPhilippBecker123HaritPandya4GregorGebhardt1ChengZhao5JamesTaylor6GerhardNeumann423Abstract1.introductioninordertointegr...
Networks Inference Recurrent High-dimensional in
2023-11-13 14:48:221158522.34 KB18
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Quantifying Generalization in Reinforcement Learning
QuantifyingGeneralizationinReinforcementLearningKarlCobbe1OlegKlimov1ChrisHesse1TaehoonKim1JohnSchulman1Abstract(Nicholetal.,2018),weseektobetterquantifyanagent’sabilitytogeneralize.inthispaper,we...
Learning Reinforcement in generalization Quantifying
2023-11-13 14:48:1916953.4 MB16
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Phase transition in PCA with missing data Reduced signal-to-noise ratio, not sample size!
PhasetransitioninPCAwithmissingdata:Reducedsignal-to-noiseratio,notsamplesize!NielsBruunIpsen1LarsKaiHansen1Abstract(1999)andthisformulationallowsforestimatingprincipalcomponentsinthepresenceofmiss...
with Data in Phase Missing
2023-11-13 14:48:141715896.19 KB14
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PAC Learnability of Node Functions in Networked Dynamical Systems
PACLearnabilityofNodeFunctionsinNetworkedDynamicalSystemsAbhijinAdiga1ChrisJ.Kuhlman1MadhavV.Marathe12S.S.Ravi13AnilK.Vullikanti12Abstract(Beietal.,2016;Kleinbergetal.,2017;Adigaetal.,2018).Weconsi...
of in Node Functions Networked
2023-11-13 14:48:11880488.38 KB21
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PAC Identification of Many Good Arms in Stochastic Multi-Armed Bandits
PACIdentiﬁcationofManyGoodArmsinStochasticMulti-ArmedBanditsArghyaRoyChaudhuri1ShivaramKalyanakrishnan1Abstractdecision,whichproducesareal-valuedreward.Therewardisdrawni.i.d.fromadistributioncorre...
of Identification in Good PAC
2023-11-13 14:48:111061497.26 KB21
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Overcoming Mean-Field Approximations in Recurrent Gaussian Process Models
OvercomingMean-FieldApproximationsinRecurrentGaussianProcessModelsAlessandroDavideIalongo12MarkvanderWilk3JamesHensman3CarlEdwardRasmussen1Abstractthedistributionoftheoutcome(vonNeumannetal.,1944)....
Gaussian Process Recurrent in Approximations
2023-11-13 14:48:119353.45 MB9
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Open-ended learning in symmetric zero-sum games
Open-endedLearninginSymmetricZero-sumGamesDavidBalduzzi1MartaGarnelo1YoramBachrach1WojciechM.Czarnecki1JulienPerolat1MaxJaderberg1ThoreGraepel1Abstractofwhattesttotake,orwhatobjectivetooptimize,isn...
Learning in Games Symmetric Zero-Sum
2023-11-13 14:48:091874772.03 KB10
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Online Convex Optimization in Adversarial Markov Decision Processes
OnlineConvexOptimizationinAdversarialMarkovDecisionProcessesAvivRosenberg1YishayMansour12AbstractWeproposeanovelalgorithmfortheadversarialMDPmodelwherethetransitionfunctionisunknowntotheWeconsidero...
Online Optimization Adversarial Markov in
2023-11-13 14:48:07884250.64 KB9
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On The Power of Curriculum Learning in Training Deep Networks
OnThePowerofCurriculumLearninginTrainingDeepNetworksGuyHacohen12DaphnaWeinshall1Abstracttypicallyreﬂectstheircomplexity.Thestudentisthengrad-uallyintroducedtotheseconceptsbyincreasingcomplexity,Tr...
Learning of on Curriculum the
2023-11-13 14:48:051424602.8 KB11
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On the Generalization Gap in Reparameterizable Reinforcement Learning
OntheGeneralizationGapinReparameterizableReinforcementLearningHuanWang1StephanZheng1CaimingXiong1RichardSocher1Abstract2018a).Amodelthatperformswellinthetrainingenvi-ronment,mayormaynotperformwellw...
gap Reinforcement on the in
2023-11-13 14:48:05711341.43 KB20
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On Sparse Linear Regression in the Local Differential Privacy Model
OnSparseLinearRegressionintheLocalDifferentialPrivacyModelDiWang1JinhuiXu1Abstractsciences(Marascuilo&Serlin,1988),genomicsresearch(Bu˘žková,2013)andsignalrecovery(Bühlmann&Vaninthispaper,westu...
Sparse on Local Regression the
2023-11-13 14:48:031048962.15 KB22
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On Connected Sublevel Sets in Deep Learning
OnConnectedSublevelSetsinDeepLearningQuynhNguyen1Abstractcontinuouspathfromanystartingpointinparameterspaceonwhichthelossisnon-increasingandgetsarbitrarilycloseThispapershowsthateverysublevelsetoft...
Learning on Deep in Connected
2023-11-13 14:48:01894369.75 KB6
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Natural Analysts in Adaptive Data Analysis
NaturalAnalystsinAdaptiveDataAnalysisTijanaZrnic1MoritzHardt1Abstract1.introductionAdaptivedataanalysisisfrequentlycriticizedforModerndataanalysisisusuallyadaptiveinthesensethatitspessimisticgenera...
Adaptive Analysis Data in Natural
2023-11-13 14:47:561027298.81 KB5
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Measurements of Three-Level Hierarchical Structure in the Outliers in the Spectrum of Deepnet Hessians
MeasurementsofThree-LevelHierarchicalStructureintheOutliersintheSpectrumofDeepnetHessiansVardanPapyan1Abstract(f(xi,c;θ),yc)∈R+isthecross-entropylossbetweenthesoftmaxoff(xi,c;θ)andtheone-hotvect...
of the Hierarchical in Structure
2023-11-13 14:47:5019379.13 MB28
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Matrix-Free Preconditioning in Online Learning
Matrix-FreePreconditioninginOnlineLearningAshokCutkosky1TamasSarlos1AbstractOurgoalistoobtainadaptiveregretboundssothatRT(w˚)maybemuchsmallerineasierproblemswhilestillmaintain-Weprovideanonlinecon...
Learning Online in Matrix-Free Preconditioning
2023-11-13 14:47:486981.74 MB28
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Leveraging Low-Rank Relations Between Surrogate Tasks in Structured Prediction
LeveragingLow-RankRelationsBetweenSurrogateTasksinStructuredPredictionGiuliaLuise1DimitrisStamos1MassimilianoPontil12CarloCiliberto13AbstractAmongthemostwell-establishedstrategiesforstructuredpredi...
Low-Rank in Relations Leveraging Tasks
2023-11-13 14:47:45987954.57 KB17
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Lexicographic and Depth-Sensitive Margins in Homogeneous and Non-Homogeneous Deep Models
LexicographicandDepth-SensitiveMarginsinHomogeneousandNon-HomogeneousDeepModelsMorShpigelNacson1SuriyaGunasekar2JasonD.Lee3NathanSrebro2DanielSoudry1Abstractimaofthetraininglossindeedhaveveryhighte...
and in Lexicographic Depth-Sensitive Margins
2023-11-13 14:47:45887313.42 KB11
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Learning to Route in Similarity Graphs
LearningtoRouteinSimilarityGraphsDmitryBaranchuk12DmitryPersiyanov3AntonSinitsin14ArtemBabenko14AbstractThecurrentapproachesforefﬁcientNNSmostlybelongtothreeseparatelinesofresearch.Theﬁrstfamilyo...
Learning graphs in to Similarity
2023-11-13 14:47:431596896.97 KB5
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Learning to Exploit Long-term Relational Dependencies in Knowledge Graphs
LearningtoExploitLong-termRelationalDependenciesinKnowledgeGraphsLingbingGuo1ZequnSun1WeiHu1Abstractsamereal-worldobject;and(ii)KGcompletion,a.k.a.linkprediction,whichaimstocompletethemissingfactsi...
Learning Dependencies in to Relational
2023-11-13 14:47:421013634.07 KB6
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