FoundationsofMachineLearning(1)英文文献资料.pdf

FoundationsofMachineLearning(1)英文文献资料.pdf

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时间:2019-07-02

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1、FoundationsofMachineLearningAdaptiveComputationandMachineLearningThomasDietterich,EditorChristopherBishop,DavidHeckerman,MichaelJordan,andMichaelKearns,AssociateEditorsAcompletelistofbookspublishedinTheAdaptiveComputationsandMachineLearningseriesappearsatt

2、hebackofthisbook.FoundationsofMachineLearningMehryarMohri,AfshinRostamizadeh,andAmeetTalwalkarTheMITPressCambridge,MassachusettsLondon,Englandc2012MassachusettsInstituteofTechnologyAllrightsreserved.Nopartofthisbookmaybereproducedinanyformbyanyelectronico

3、rmechanicalmeans(includingphotocopying,recording,orinformationstorageandretrieval)withoutpermissioninwritingfromthepublisher.MITPressbooksmaybepurchasedatspecialquantitydiscountsforbusinessorsalespromotionaluse.Forinformation,pleaseemailspecialsales@mitpre

4、ss.mit.eduorwritetoSpecialSalesDepartment,TheMITPress,55HaywardStreet,Cam-bridge,MA02142.ThisbookwassetinLATEXbytheauthors.PrintedandboundintheUnitedStatesofAmerica.LibraryofCongressCataloging-in-PublicationDataMohri,Mehryar.Foundationsofmachinelearning/Me

5、hryarMohri,AfshinRostamizadeh,andAmeetTalwalkar.p.cm.-(Adaptivecomputationandmachinelearningseries)Includesbibliographicalreferencesandindex.ISBN978-0-262-01825-8(hardcover:alk.paper)1.Machinelearning.2.Computeralgorithms.I.Rostamizadeh,Afshin.II.Talwalkar

6、,Ameet.III.Title.Q325.5.M642012006.3’1-dc23201200724910987654321ContentsPrefacexi1Introduction11.1Applicationsandproblems........................11.2Definitionsandterminology.......................31.3Cross-validation..............................51.4Learni

7、ngscenarios............................71.5Outline..................................82ThePACLearningFramework112.1ThePAClearningmodel.........................112.2Guaranteesforfinitehypothesissets—consistentcase........172.3Guaranteesforfinitehypothesissets—

8、inconsistentcase.......212.4Generalities................................242.4.1Deterministicversusstochasticscenarios............242.4.2Bayeserrorandnoise......................252.4.3Estimationandapproximatio

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