Konferenzschrift | Kongress
Statistical learning theory and stochastic optimization
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 asis 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. TOC: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.
- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- ISBN
-
9783540225720
3540225722
- Maße
-
24 cm
- Umfang
-
VIII, 272 S.
- Sprache
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Englisch
- Anmerkungen
-
graph. Darst.
Literaturangaben
- Erschienen in
-
Lecture notes in mathematics ; Vol. 1851
- Klassifikation
-
Mathematik
- Schlagwort
-
Mathematische Lerntheorie
Stochastische Optimierung
- Ereignis
-
Veröffentlichung
- (wo)
-
Berlin, Heidelberg, New York
- (wer)
-
Springer
- (wann)
-
2004
- Beteiligte Personen und Organisationen
-
Catoni, Olivier
Picard, Jean
Ecole d'Eté de Probabilités (31 : 2001 : Saint-Flour)
- Inhaltsverzeichnis
- Rechteinformation
-
Bei diesem Objekt liegt nur das Inhaltsverzeichnis digital vor. Der Zugriff darauf ist unbeschränkt möglich.
- Letzte Aktualisierung
-
11.03.2025, 12:09 MEZ
Datenpartner
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Konferenzschrift
- Kongress
Beteiligte
- Catoni, Olivier
- Picard, Jean
- Ecole d'Eté de Probabilités (31 : 2001 : Saint-Flour)
- Springer
Entstanden
- 2004
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