ExtremeMulti-labelClassificationfromAggregatedLabelsYanyaoShen1Hsiang-fuYu2SujaySanghavi12InderjitDhillon23Abstractitybecomesgrowinglyexpensive.Asaresult,modernma-chinelearningapplicationsneedtodea...
ConvexCalibratedSurrogatesfortheMulti-labelF-MeasureMingyuanZhang1HarishG.Ramaswamy2ShivaniAgarwal1Abstract1.IntroductionTheF-measureisawidelyusedperformanceTheFβ-measureisawidelyusedperformanceme...
SparseExtremeMulti-labelLearningwithOraclePropertyWeiweiLiu1XiaoboShen2Abstractdingapproaches(Hsuetal.,2009;Yuetal.,2014;Prabhu&Varma,2014;Liu&Tsang,2015a;Bhatiaetal.,2015;Thepioneeringworkofsparse...
LearningContext-DependentLabelPermutationsforMulti-labelClassificationJinseokNam1Young-BumKim1EneldoLozaMenc´ıa2SunghyunPark1RuhiSarikaya1JohannesFu¨rnkranz2AbstractofCCsisthattheyrequireafixeds...
HierarchicalMulti-labelClassificationNetworksJônatasWehrmann1RicardoCerri2RodrigoC.Barros1AbstractInamorechallengingscenario,thereareHCproblemsinwhicheachobjectcanbeassociatedtoseveraldifferentOne...
AUnifiedViewofMulti-labelPerformanceMeasuresXi-ZhuWu1Zhi-HuaZhou1Abstracteachinstancecanbeassociatedwithmultiplelabelssimul-taneously.Forexample,itisdifficulttotellwhichmistakeMulti-labelclassifica...
ScalableGenerativeModelsforMulti-labelLearningwithMissingLabelsVikasJain1NirbhayModhe1PiyushRai1Abstracttisingandrecommendersystems(Prabhu&Varma,2014;Jainetal.,2016),etc.Wepresentascalable,generati...