"on"的相关文档

标签“on”的相关文档，共225条

on hyperparameter tuning in general clustering problemsm
onhyperparametertuningingeneralclusteringproblemsXinjieFan1YuguangYue1PurnamritaSarkar1Y.X.RachelWang2Abstractsiblehyperparametervaluesandoftenhastorelyongoodheuristicsanddomainknowledgefromtheuser...
on in Clustering General Hyperparameter
2023-11-14 21:45:2917971.02 MB16
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on Gradient Descent Ascent for Nonconvex-Concave Minimax Problems
onGradientDescentAscentforNonconvex-ConcaveMinimaxProblemsTianyiLin1ChiJin2Michael.I.Jordan3Abstractincludinggenerativeadversarialnetworks(GANs)(Good-fellowetal.,2014),statistics(Xuetal.,2009;Abade...
for Gradient Descent on Minimax
2023-11-14 21:45:29865561.62 KB24
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on Efficient Constructions of Checkpoints
onEfﬁcientConstructionsofCheckpointsYuChen1ZhenmingLiu1BinRen1XinJin2AbstractProducingcheckpointsfrequentlyenablesfailedtrainingprocesstorestartwithminimumwastedtime,andservesEfﬁcientconstruction...
of Efficient on Constructions Checkpoints
2023-11-14 21:45:295408.58 MB12
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on Differentially Private Stochastic Convex Optimization with Heavy-tailed Data
onDifferentiallyPrivateStochasticConvexOptimizationwithHeavy-tailedDataDiWang12HanshenXiao3SriniDevadas3JinhuiXu1Abstractarethemostfundamentalproblemsinsupervisedlearningandstatistics.Theyﬁndnumer...
Optimization with on Stochastic Convex
2023-11-14 21:45:281156360.77 KB2
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on Efficient Low Distortion Ultrametric Embedding
onEfﬁcientLowDistortionUltrametricEmbeddingVincentCohen-Addad1KarthikC.S.2GuillaumeLagarde3Abstract1.IntroductionAclassicprobleminunsupervisedlearningandThecurseofdimensionalityhasruthlesslybeenha...
Efficient on low embedding Distortion
2023-11-14 21:45:281268281.08 KB20
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on Convergence-Diagnostic based Step Sizes for Stochastic Gradient Descent
onConvergence-DiagnosticbasedStepSizesforStochasticGradientDescentScottPesme1AymericDieuleveut2NicolasFlammarion1Abstractwarmrestarts(Loshchilov&Hutter,2016).Howeverthosestrategiestypicallydonotcom...
for on Stochastic Based Step
2023-11-14 21:45:281130800.97 KB27
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on Coresets for Regularized Regression
onCoresetsforRegularizedRegressionRachitChhaya1AnirbanDasgupta1SupratimShit1Abstractusuallyindependentofthesizeoftheoriginaldatasetmak-ingtrainingonthemmuchquicker.SamplingbasedcoresetsWestudytheef...
for on Regression Coresets Regularized
2023-11-14 21:45:27540379.77 KB2
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on Contrastive Learning for Likelihood-free Inference
onContrastiveLearningforLikelihood-freeInferenceConorDurkan1IainMurray1GeorgePapamakarios2Abstractbasedonneuralnetworkshavereducedthenumberofsim-ulationsneededtoperformeffectiveinferencebyordersLik...
Learning for Inference on Contrastive
2023-11-14 21:45:2711731.07 MB20
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on a projective ensemble approach to two sample test for equality of distributions
onaProjectiveEnsembleApproachtoTwoSampleTestforEqualityofDistributionsZhimeiLi1YaowuZhang1Abstracttestingfortheequalityoftwodistributions,i.e.,Inthiswork,weproposearobusttestforthemul-H0:F=GversusH...
on to Approach Sample Two
2023-11-14 21:45:27513319.49 KB13
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on conditional versus marginal bias in multi-armed bandits
onconditionalversusmarginalbiasinmulti-armedbanditsJaehyeokShin1AlessandroRinaldo1AadityaRamdas12AbstractThedataarecollectedsequentiallyinstages,duringwhichtheanalystdrawsasamplefromoneamongﬁnitel...
on in Conditional Multi-armed Bias
2023-11-14 21:45:271542687.29 KB25
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on Breaking Deep Generative Model-based Defenses and Beyond
onBreakingDeepGenerativeModel-basedDefensesandBeyondYanzhiChen1RenjieXie2ZhanxingZhu3Abstract2018),featuredenoising(Liaoetal.,2018;Xieetal.,2019),randomizedsmoothing(Salmanetal.,2019;Cohenetal.,Dee...
and Generative on Deep Breaking
2023-11-14 21:45:27890664.01 KB29
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Normalizing Flows on Tori and Spheres
NormalizingFlowsonToriandSpheresDaniloJimenezRezende1GeorgePapamakarios1Se´bastienRacanie`re1MichaelS.Albergo2GurtejKanwar3PhialaE.Shanahan3KyleCranmer2AbstractAnormalizingﬂowimplementstwooperati...
and on Normalizing Flows Tori
2023-11-14 21:45:2616321.66 MB11
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Learning Quadratic Games on Networks
LearningQuadraticGamesonNetworksYanLeng1XiaowenDong2JunfengWu3AlexPantland4AbstractFacebook,onlytoﬁndoutthatanypairofFacebookuserscanactuallybeconnectedviaapproximatelythreeandahalfIndividuals,oro...
Learning Networks on Games Quadratic
2023-11-14 21:44:551438775 KB13
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Influenza Forecasting Framework based on Gaussian Processes
InﬂuenzaForecastingFrameworkbasedonGaussianProcessesChristophZimmer1RezaYaesoubi2AbstractintoresearchonforecastingInﬂuenza.Thisincludesestab-lishingachallengetoforecastinﬂuenzaactivities.InthisT...
on Gaussian Processes Based Framework
2023-11-14 21:44:391593255.49 KB1
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Improved Bounds on Minimax Regret under Logarithmic Loss via Self-Concordance
ImprovedBoundsonMinimaxRegretunderLogarithmicLossviaSelf-ConcordanceBlairBilodeau123DylanJ.Foster4DanielM.Roy123AbstractTheloglosspenalizestheplayerbasedonhowmuchprob-abilitymasstheyplaceontheactua...
on under Regret bounds Improved
2023-11-14 21:44:341058393.3 KB18
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Few-shot Relation Extraction via Bayesian Meta-learning on Task Graphs
Few-shotRelationExtractionviaBayesianMeta-learningonRelationGraphsMengQu12TianyuGao3Louis-PascalA.C.Xhonneux12JianTang145Abstracttomaticallygeneratetrainingdata.Forexample,givenatriplet(Washington,...
on Bayesian via Meta-Learning Few-shot
2023-11-14 21:44:145882.01 MB30
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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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Evaluating Machine Accuracy on ImageNet
EvaluatingMachineAccuracyonImageNetVaishaalShankar1RebeccaRoelofs2HoriaMania1AlexFang1BenjaminRecht1LudwigSchmidt1AbstractInthispaper,wecontextualizeprogressonImageNetbycomparingawiderangeofImageNe...
on Machine Evaluating Accuracy ImageNet
2023-11-14 21:44:056971.62 MB16
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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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Efficient nonparametric statistical inference on population feature importance using Shapley values
EfﬁcientnonparametricstatisticalinferenceonpopulationfeatureimportanceusingShapleyvaluesBrianD.Williamson1JeanFeng2AbstractLikewise,vaccineresearchersmaywanttoknowthemostimportantmolecularphenotyp...
Efficient Inference Feature Population on
2023-11-14 21:43:5911182.38 MB6
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