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Statistical learning theory and stochastic optimization : Ecole d'Eté de Probabilités de Saint-Flour XXXI-2001

Autor: Olivier Catoni; Jean Picard; LINK (Online service)
Editora: Berlin : Springer-Verlag, ©2004.
Séries: Lecture notes in mathematics (Springer-Verlag), 1851.
Edição/Formato   e-book : Documento : Publicação de conferência : InglêsVer todas as edições e formatos
Base de Dados:WorldCat
Resumo:
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  Ler mais...
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Detalhes

Gênero/Forma: Electronic books
Conference proceedings
Congresses
Formato Físico Adicional: Print version:
Catoni, Olivier.
Statistical learning theory and stochastic optimization.
Berlin : Springer-Verlag, ©2004
(DLC) 2004109143
(OCoLC)56714791
Tipo de Material: Publicação de conferência, Documento, Recurso Internet
Tipo de Documento: Recurso Internet, Arquivo de Computador
Todos os Autores / Contribuintes: Olivier Catoni; Jean Picard; LINK (Online service)
ISBN: 9783540445074 3540445072
Número OCLC: 56508135
Notas: " ... 31st Probability Summer School in Saint-Flour (July 8-25, 2001) ..."--Preface.
Descrição: 1 online resource (viii, 272 pages) : illustrations.
Conteúdos: 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.
Título da Série: Lecture notes in mathematics (Springer-Verlag), 1851.
Outros Títulos: Ecole d'Eté de Probabilités de Saint-Flour XXXI-2001
Responsabilidade: Olivier Catoni ; editor, Jean Picard.
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Resumo:

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  Ler mais...

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From the reviews: "This book is based on a course of lectures given by the author on a circle of ideas lying at the interface of information theory, statistical learning theory and statistical Ler mais...

 
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