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1、StatisticalMachineLearningforDataMiningandCollaborativeMultimediaRetrievalHOI,ChuHong(Steven)AThesisSubmittedinPartialFulfilmentoftheRequirementsfortheDegreeofDoctorofPhilosophyinComputerScienceandEngineeringcTheChineseUniversityofHongKongSeptember2006TheChines
2、eUniversityofHongKongholdsthecopyrightofthisthesis.Anyperson(s)intendingtouseapartorwholeofthematerialsinthethesisinaproposedpublicationmustseekcopyrightreleasefromtheDeanoftheGraduateSchool.Thesis/AssessmentCommitteeMembersProfessorTien-TsinWong(Chair)Professo
3、rMichaelR.Lyu(ThesisSupervisor)ProfessorLeoJiayaJia(CommitteeMember)ProfessorEdwardY.Chang(ExternalExaminer)Abstractofthesisentitled:StatisticalMachineLearningforDataMiningandCollaborativeMul-timediaRetrievalSubmittedbyHOI,ChuHong(Steven)forthedegreeofDoctorofP
4、hilosophyatTheChineseUniversityofHongKonginSeptember2006Statisticalmachinelearningtechniqueshavebeenwidelyappliedindataminingandmultimediainformationretrieval.Whiletradi-tionalmethods,suchassupervisedlearning,unsupervisedlearning,andactivelearning,havebeenexten
5、sivelystudiedseparately,therearefewcomprehensiveschemestoinvestigatethesetechniquesinaunifiedapproach.Thisthesisproposesaunifiedlearningparadigm(ULP)frameworkthatintegratesseveralmachinelearningtechniquesincludingsupervisedlearning,unsupervisedlearning,semi-super
6、visedlearning,activelearningandmetriclearninginasynergisticwaytomaximizetheeffectivenessofalearningtask.Basedonthisunifiedlearningframework,anovelschemeissug-gestedforlearningUnifiedKernelMachines(UKM).TheUKMschemecombinessupervisedkernelmachinelearning,unsupervis
7、edkernelde-sign,semi-supervisedkernellearning,andactivelearninginaneffec-tivefashion.AkeycomponentintheUKMschemeistolearnkernelsfrombothlabeledandunlabeleddata.Tothispurpose,anewSpectralKernelLearning(SKL)algorithmisproposed,whichisrelatedtoaquadraticprogram.Emp
8、iricalresultsshowthattheUKMtechniqueispromisingforclassificationtasks.iWithintheunifiedlearningframework,thisthesisfurtherexplorestwoimportantchallengingtasks.OneisBatchModeAc