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标签“of”的相关文档，共557条

Fine-Grained Analysis of Stability and Generalization for Stochastic Gradient Descent
Fine-GrainedAnalysisofStabilityandGeneralizationforStochasticGradientDescentYunwenLei12YimingYing3Abstractaniterativealgorithm,SGDupdatesthemodelsequentiallyuponreceivinganewdatumwithacheapper-iter...
of for and Stability Analysis
2023-11-14 21:44:15599368.85 KB22
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Fast Learning of Graph Neural Networks with Guaranteed Generalizability One-hidden-layer Case
FastLearningofGraphNeuralNetworkswithGuaranteedGeneralizability:One-hidden-layerCaseShuaiZhang1MengWang1SijiaLiu2Pin-YuChen3JinjunXiong3Abstract1.IntroductionAlthoughgraphneuralnetworks(GNNs)haveGr...
Learning of Neural Networks with
2023-11-14 21:44:12652739.83 KB18
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Fast computation of Nash Equilibria in Imperfect Information Games
FastComputationofNashEquilibriainImperfectInformationGamesRemiMunos1JulienPerolat1Jean-BaptisteLespiau1MarkRowland1BartDeVylder1MarcLanctot1FinbarrTimbers1DanielHennes1ShayeganOmidshaﬁei1AudrunasG...
of in Fast Computation Nash
2023-11-14 21:44:111355364.28 KB15
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Fast and Consistent Learning of Hidden Markov Models by Incorporating Non-Consecutive Correlations
FastandConsistentLearningofHiddenMarkovModelsbyIncorporatingNon-ConsecutiveCorrelationsRobertMattila1CristianR.Rojas1EricMoulines23VikramKrishnamurthy4BoWahlberg1Abstractcomputationalbiology(Durbin...
Learning of and Hidden Markov
2023-11-14 21:44:11590580.64 KB4
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Explore, Discover and Learn Unsupervised Discovery of State-Covering Skills
Explore,DiscoverandLearn:UnsupervisedDiscoveryofState-CoveringSkillsV´ıctorCampos1AlexTrott2CaimingXiong2RichardSocher2XavierGiro-i-Nieto3JordiTorres1AbstractFigure1.Skillslearnedonamazewithbottl...
of and Unsupervised Discovery Learn
2023-11-14 21:44:0815403.29 MB29
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Explaining Groups of Points in Low-Dimensional Representations
ExplainingGroupsofPointsinLow-DimensionalRepresentationsGregoryPlumb1JonathanTerhorst2SriramSankararaman3AmeetTalwalkar14AbstractFigure1:Arepresentationlearnedforasingle-cellRNAsequencedatasetusing...
of Representations in Points Low-Dimensional
2023-11-14 21:44:078111.6 MB18
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Evaluating the Performance of Reinforcement Learning Algorithms
EvaluatingthePerformanceofReinforcementLearningAlgorithmsScottM.Jordan1YashChandak1DanielCohen1MengxueZhang1PhilipS.Thomas1AbstractusabilityofRLalgorithms,wesuggestthatitshouldhavefourproperties.Fi...
Learning of Algorithms Reinforcement the
2023-11-14 21:44:0613829.01 MB29
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Evaluating Lossy Compression Rates of Deep Generative Models
EvaluatingLossyCompressionRatesofDeepGenerativeModelsSicongHuang123AlirezaMakhzani12YanshuaiCao3RogerGrosse12Abstracttance(FID)(Heuseletal.,2017),whichdonothavenearlythesamedegreeoftheoreticalunder...
of Generative Deep Evaluating Compression
2023-11-14 21:44:057296.12 MB7
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Estimation of Bounds on Potential Outcomes For Decision Making
EstimationofBoundsonPotentialOutcomesForDecisionMakingMaggieMakar1FredrikJohansson2JohnGuttag1DavidSontag1Abstractneedstoknowifthepotentialoutcomesundertreatmentandnon-treatmentfallwithin2–3.Learn...
of for on Estimation bounds
2023-11-14 21:44:05523786.84 KB8
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Estimating the Number and Effect Sizes of Non-null Hypotheses
EstimatingtheNumberandEffectSizesofNon-nullHypothesesJenniferBrennan1RamyaKorlakaiVinayak1KevinJamieson1AbstractForexample,supposeascientistwouldliketotest10,000Westudytheproblemofestimatingthedist...
of and the Estimating effect
2023-11-14 21:44:0518923.23 MB24
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Estimating the Error of Randomized Newton Methods A Bootstrap Approach
EstimatingtheErrorofRandomizedNewtonMethods:ABootstrapApproachJessieX.T.Chen1MilesE.Lopes2AbstractresearchhasbeendrivenbythefactthatcomputinganinverseHessiantomachineprecisioncanbeverycostlyRandomi...
of Newton Methods the Estimating
2023-11-14 21:44:041358471.21 KB20
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Error-Bounded Correction of Noisy Labels
Error-BoundedCorrectionofNoisyLabelsSongzhuZheng1PengxiangWu2AmanGoswami3MayankGoswami4DimitrisMetaxas2ChaoChen5Abstract&GeoffreyE.,2012;Wuetal.,2018).Tocollectlargescaleannotateddata,itisin-Manyme...
of Labels Noisy Correction Error-Bounded
2023-11-14 21:44:04853658.28 KB22
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Estimating Model Uncertainty of Neural Network in Sparse Information Form
EstimatingModelUncertaintyofNeuralNetworksinSparseInformationFormJongseokLee1MatthiasHumt1JianxiangFeng12RudolphTriebel12Abstractferencewhatlinearmapsareforalgebra.Forexample,oncetheposteriordistri...
of Neural Model in Network
2023-11-14 21:44:047711.15 MB15
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Empirical Study of the Benefits of Overparameterization in Learning Latent Variable Models
EmpiricalStudyoftheBeneﬁtsofOverparameterizationinLearningLatentVariableModelsRares-DariusBuhai1YoniHalpern2YoonKim3AndrejRisteski4DavidSontag1Abstractgoalisfrequentlytoconﬁrmorrejectwhetherapart...
of the in Empirical Study
2023-11-14 21:44:021960901.81 KB9
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Emergence of Separable Manifolds in Deep Language Representations
EmergenceofSeparableManifoldsinDeepLanguageRepresentationsJonathanMamou1HangLe2MiguelADelRio2CoryStephenson1HanlinTang1YoonKim3SueYeonChung24Abstract1.IntroductionandRelatedWorkDeepneuralnetworks(D...
of Deep in Manifolds Language
2023-11-14 21:44:0218467.44 MB20
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Eliminating the Invariance on the Loss Landscape of Linear Autoencoders
EliminatingtheInvarianceontheLossLandscapeofLinearAutoencodersRezaoftadeh1JiayiShen1ZhangyangWang1DylanShell1Abstractgenerallythecategorizationofextremepoints,hasﬂour-ished.Muchworkextendstheresul...
of on the Loss Invariance
2023-11-14 21:44:01887580.69 KB20
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Einsum Networks Fast and Scalable Learning of Tractable Probabilistic Circuits
EinsumNetworks:FastandScalableLearningofTractableProbabilisticCircuitsRobertPeharz1StevenLang2AntonioVergari3KarlStelzner2AlejandroMolina2MartinTrapp4GuyVandenBroeck3KristianKersting2ZoubinGhahrama...
Learning of Networks and Fast
2023-11-14 21:44:015344.93 MB22
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Efficient proximal mapping of the path-norm regularizer of shallow networks
EfﬁcientProximalMappingofthe1-path-normofShallowNetworksFabianLatore1PaulRolland1NadavHallak1VolkanCevher1AbstracttheLipschitzconstantofthenetworkfunctiontoquantizerobustness,andregularizationtoen...
of Efficient the Proximal Regularizer
2023-11-14 21:43:591420487.77 KB21
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Dynamics of Deep Neural Networks and Neural Tangent Hierarchy
DynamicsofDeepNeuralNetworksandNeuralTangentHierarchyJiaoyangHuang1Horng-TzerYau2Abstractproblems,thereisnoguaranteethatagradientbasedalgo-rithmwillbeabletoﬁndtheoptimalparametersefﬁcientlyTheevo...
of Neural Networks and Deep
2023-11-14 21:43:571793305.48 KB1
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Differentiable Likelihoods for Fast Inversion of Likelihood-Free Dynamical Systems
DifferentiableLikelihoodsforFastInversionof‘Likelihood-Free’DynamicalSystemsHansKersting123NicholasKra¨mer1MartinSchiegg3ChristianDaniel3MichaelTiemann3PhilippHennig12AbstractFigure1.Inferenceon...
of for Fast Differentiable Likelihood-Free
2023-11-14 21:43:4817771.31 MB7
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