PersonalizedFederatedLearningusingHypernetworksAvivShamsian∗1AvivNavon∗1EthanFetaya1GalChechik12Abstractwhileminimizingcommunication.Unfortunately,learningasingleglobalmodelmayfailwhenthedatadist...
ModelFusionforPersonalizedLearningChiThanhLam1TrongNghiaHoang2BryanKianHsiangLow1PatrickJaillet3Abstract(Finnetal.,2017;Yoonetal.,2018)andPersonalizedfeder-atedlearning(Fallahetal.,2020;Dinhetal.,2...
ModelDistillationforRevenueOptimization:InterpretablePersonalizedPricingMaxBiggs1WeiSun2MarkusEttl2Abstractmainconcernsisthatthemostaccuratepredictionmodelsareoftennon-parametricfunctionswhichareco...
ExploitingSharedRepresentationsforPersonalizedFederatedLearningLiamCollins1HamedHassani2AryanMokhtari1SanjayShakkottai1Abstracteffectivemodelsforeachclientbyleveragingthelocalcom-putationalpower,me...
DebiasingModelUpdatesforImprovingPersonalizedFederatedTrainingDurmusAlpEmreAcar1YueZhao2RuizhaoZhu1RamonMatasNavarro2MatthewMattina2PaulN.Whatmough2VenkateshSaligrama1Abstractofdevicesparticipating...
DeepCoDA:PersonalizedinterpretabilityforcompositionalhealthdataThomasP.Quinn1DangNguyen1SantuRana1SunilGupta1SvethaVenkatesh1Abstracttrust.Inthehealthcaresetting,interpretablemodelsshouldimplicater...
APersonalizedAffectiveMemoryModelforImprovingEmotionRecognitionPabloBarros1GermanI.Parisi12StefanWermter1Abstracttechniques(Ngetal.,2015;Kayaetal.,2017),neuralactiva-tionanddatadistributionregulari...