Statistical Learning Theory-notes英文学习材料

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1、CS229T/STAT231:StatisticalLearningTheory(Winter2016)PercyLiangLastupdatedWedApr20201601:36Theselecturenoteswillbeupdatedperiodicallyasthecoursegoeson.TheAppendixdescribesthebasicnotation,denitions,andtheorems.Contents1Overview41.1Whatisthiscourseabout?(Lecture1).....................41.2Asymp

2、totics(Lecture1).............................51.3Uniformconvergence(Lecture1)........................61.4Kernelmethods(Lecture1)...........................81.5Onlinelearning(Lecture1)............................92Asymptotics102.1Overview(Lecture1)...............................102.2Gaussianme

3、anestimation(Lecture1).....................112.3Multinomialestimation(Lecture1).......................132.4Exponentialfamilies(Lecture2).........................162.5Maximumentropyprinciple(Lecture2).....................192.6Methodofmomentsforlatent-variablemodels(Lecture3)..........232.7Fixe

4、ddesignlinearregression(Lecture3)....................302.8Generallossfunctionsandrandomdesign(Lecture4).............332.9Regularizedxeddesignlinearregression(Lecture4).............402.10Summary(Lecture4)...............................442.11References.....................................453Un

5、iformconvergence463.1Overview(Lecture5)...............................473.2Formalsetup(Lecture5).............................473.3Realizablenitehypothesisclasses(Lecture5).................503.4Generalizationboundsviauniformconvergence(Lecture5)..........533.5Concentrationinequalities(Lecture

6、5)......................563.6Finitehypothesisclasses(Lecture6)......................623.7Concentrationinequalities(continued)(Lecture6)...............633.8Rademachercomplexity(Lecture6).......................663.9Finitehypothesisclasses(Lecture7)......................723.10Shatteringcoecient

7、(Lecture7)........................7413.11VCdimension(Lecture7)............................763.12Norm-constrainedhypothesisclasses(Lecture7)................813.13Coveringnumbers(metricentropy)(Lecture8)................883.14Algorithmicstabilit