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作者 Catoni, Olivier
書名 Statistical learning theory and stochastic optimization [electronic resource] : Ecole d'Eté de Probabilités de Saint-Flour XXXI-2001 / Olivier Catoni ; editor, Jean Picard
出版項 Berlin : Springer-Verlag, ©2004
國際標準書號 9783540445074 (electronic bk.)
3540445072 (electronic bk.)
book jacket
說明 1 online resource (viii, 272 pages) : illustrations
text txt rdacontent
computer c rdamedia
online resource cr rdacarrier
系列 Lecture notes in mathematics, 0075-8434 ; 1851
Lecture notes in mathematics (Springer-Verlag) ; 1851
附註 Includes bibliographical references and index
" ... 31st Probability Summer School in Saint-Flour (July 8-25, 2001) ..."--Preface
Universal Lossless Data Compression -- Links Between Data Compression and Statistical Estimation -- Non Cumulated Mean Risk -- Gibbs Estimators -- Randomized Estimators and Empirical Complexity -- Deviation Inequalities -- Markov Chains with Exponential Transitions -- References -- Index
Statistical learning theory is aimed at analyzing complex data with necessarily approximate models. This book is intended for an audience with a graduate background in probability theory and statistics. It will be useful to any reader wondering why it may be a good idea, to use as is often done in practice a notoriously "wrong'' (i.e. over-simplified) model to predict, estimate or classify. This point of view takes its roots in three fields: information theory, statistical mechanics, and PAC-Bayesian theorems. Results on the large deviations of trajectories of Markov chains with rare transitions are also included. They are meant to provide a better understanding of stochastic optimization algorithms of common use in computing estimators. The author focuses on non-asymptotic bounds of the statistical risk, allowing one to choose adaptively between rich and structured families of models and corresponding estimators. Two mathematical objects pervade the book: entropy and Gibbs measures. The goal is to show how to turn them into versatile and efficient technical tools, that will stimulate further studies and results
Description based on print version record
鏈接 Print version: Catoni, Olivier. Statistical learning theory and stochastic optimization. Berlin : Springer-Verlag, ©2004 3540225722 (DLC) 2004109143 (OCoLC)56714791
主題 Probabilities -- Congresses
Mathematical statistics -- Congresses
Statistics -- Congresses
Mathematical statistics. fast (OCoLC)fst01012127
Probabilities. fast (OCoLC)fst01077737
Statistics. fast (OCoLC)fst01132103
Electronic books
Conference proceedings. fast (OCoLC)fst01423772
Alt Author Picard, Jean
Ecole d'été de probabilités de Saint-Flour (31st : 2001)
LINK (Online service)
Alt Title Ecole d'Eté de Probabilités de Saint-Flour XXXI-2001
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