"Regression"的相关文档

标签“Regression”的相关文档，共56条

Optimal Tuning for Divide-and-conquer Kernel Ridge Regression with Massive Data
OptimalTuningforDivide-and-conquerKernelRidgeRegressionwithMassiveDataGanggangXu1ZuofengShang2GuangCheng3AbstractproventobeeffectiveinLinearmodels(Chen&Xie,2014;Luetal.,2016),Partiallylinearmodels(...
for Kernel Regression Optimal Ridge
2023-11-13 12:00:221862324.76 KB6
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Nonparametric Regression with Comparisons Escaping the Curse of Dimensionality with Ordinal Information
NonparametricRegressionwithComparisons:EscapingtheCurseofDimensionalitywithOrdinalInformationYichongXu1HariankMuthakana1SivaramanBalakrishnan2ArturDubrawski3AartiSingh1AbstractRd×R,invarioustaskso...
with Regression the Nonparametric Comparisons
2023-11-13 12:00:165133.97 MB28
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Nonconvex Optimization for Regression with Fairness Constraints
NonconvexOptimizationforRegressionwithFairnessConstraintsJunpeiKomiyama1AkikoTakeda12JunyaHonda12HajimeShimao3Abstractindefaultingonloans,directapplicationofmachinelearn-ingalgorithmwouldhighlylike...
for Optimization with Regression Fairness
2023-11-13 12:00:161257294.08 KB5
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Improving Regression Performance with Distributional Losses
ImprovingRegressionPerformancewithDistributionalLossesEhsanImani1MarthaWhite1AbstractorabsoluteerrorforRegression—butthoselossesarenotnecessarilydirectlyminimized.Thereisgrowingevidencethatconvert...
with Regression Improving Losses Distributional
2023-11-13 11:59:475331.28 MB28
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Distributed Nonparametric Regression under Communication Constraints
DistributedNonparametricRegressionunderCommunicationConstraintsYuanchengZhu1JohnLafferty2Abstractaggregatedfromthemultiplelocationstoformtheﬁnalesti-mate.However,thecommunicationbetweenmachinesmay...
Distributed Regression under Communication Nonparametric
2023-11-13 11:59:291152355.81 KB3
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Detecting non-causal artifacts in multivariate linear Regression models
Detectingnon-causalartifactsinmultivariatelinearRegressionmodelsDominikJanzing1BernhardScho¨lkopf2AbstractZZZWeconsiderlinearmodelswheredpotentialXYXYXYcausesX1,...,Xdarecorrelatedwithonetargetqua...
Regression in Linear Multivariate Detecting
2023-11-13 11:59:261304368.88 KB23
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An Iterative, Sketching-based Framework for Ridge Regression
AnIterative,Sketching-basedFrameworkforRidgeRegressionAgnivaChowdhury1JiasenYang1PetrosDrineas2Abstractsion.First,whendn,i.e.,thenumberofpredictorvari-ablesdgreatlyexceedsthenumberofobservationsn,...
for An Regression Iterative Ridge
2023-11-13 11:59:0316922.04 MB10
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Adversarial Regression with Multiple Learners
AdversarialRegressionwithMultipleLearners1121LiangTongSixieYuScottAlfeldYevgeniyVorobeychikAbstractecologyofattacktargetsreﬂectsnotasinglelearner,butmanysuchlearners,allmakingautonomousdecisionsab...
Adversarial with Regression Multiple Learners
2023-11-13 11:59:001614774.3 KB24
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Active Heteroscedastic Regression
ActiveHeteroscedasticRegressionKamalikaChaudhuri1PrateekJain2NagarajanNatarajan2Abstractexample,whenthereisagroundtruthclassiﬁerthatinducesalabelingandtheoracle’sresponsesareperturbedversionsAnac...
Active Regression Heteroscedastic
2023-11-12 20:45:36764295.09 KB11
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Sketched Ridge Regression Optimization Perspective, Statistical Perspective, and Model Averaging
SketchedRidgeRegression:OptimizationPerspective,StatisticalPerspective,andModelAveragingShusenWang1AlexGittens2MichaelW.Mahoney1Abstractlemwhilegreatlymitigatingthestatisticalrisksincurredbysketchi...
Optimization and Regression Statistical Ridge
2023-11-12 20:45:151102584.01 KB4
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Rule-Enhanced Penalized Regression by Column Generation using Rectangular Maximum Agreement
Rule-EnhancedPenalizedRegressionbyColumnGenerationusingRectangularMaximumAgreementJonathanEckstein1NoamGoldberg2AiKagawa3Abstractaparticularfunctionalformforfˆ(x)(forexample,anafﬁnefunctionofx)an...
Using Generation by Regression Rule-Enhanced
2023-11-12 20:45:1012121.62 MB10
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Random Fourier Features for Kernel Ridge Regression Approximation Bounds and Statistical Guarantees
RandomFourierFeaturesforKernelRidgeRegression:ApproximationBoundsandStatisticalGuaranteesHaimAvron1MichaelKapralov2CameronMusco3ChristopherMusco3AmeyaVelingker2AmirZandieh2AbstractIntheabove,K2Rn⇥...
for Kernel Regression random Features
2023-11-12 20:45:051525557.73 KB5
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High-Dimensional Structured Quantile Regression
High-DimensionalStructuredQuantileRegressionVidyashankarSivakumar1ArindamBanerjee1Abstract2016;Vershynin,2015).Suchmodelshavebeenextendedtogeneralizedlinearmodels(Banerjeeetal.,2014;Ne-Quantileregr...
Regression High-dimensional Structured Quantile
2023-11-12 20:44:301824767.45 KB17
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Forest-type Regression with General Losses and Robust Forest
Forest-typeRegressionwithGeneralLossesandRobustForestAlexanderHanboLi1AndrewMartin2Abstractdictquantilesbydiscoveringthatbesidescalculatingtheweightedmeanoftheobservedresponsevariables,oneThispaper...
and with Regression Robust Forest-type
2023-11-12 20:44:251004550.15 KB2
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Faster Principal Component Regression and Stable Matrix Chebyshev Approximation
FasterPrincipalComponentRegressionandStableMatrixChebyshevApproximationZeyuanAllen-Zhu1YuanzhiLi2AbstracttasksofPCPandPCRbecometrivialbecausetheprojec-tionmatrixcanbeconstructedexplicitly.Wesolvepr...
Matrix and Regression Principal Component
2023-11-12 20:44:241457490.91 KB19
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Asynchronous Distributed Variational Gaussian Process for Regression
AsynchronousDistributedVariationalGaussianProcessforRegressionHaoPeng1ShandianZhe1XiaoZhang1YuanQi2Abstractmodelsistheirexpensivecomputationalcost:exactGPin-ferencerequiresO(n3)timecomplexityandO(n...
for Distributed Variational Asynchronous Gaussian
2023-11-12 20:43:53617637.79 KB17
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