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Algorithmic Learning Theory
Details
This book constitutes the refereed proceedings of the 23rd International Conference on Algorithmic Learning Theory, ALT 2012, held in Lyon, France, in October 2012. The conference was co-located and held in parallel with the 15th International Conference on Discovery Science, DS 2012. The 23 full papers and 5 invited talks presented were carefully reviewed and selected from 47 submissions. The papers are organized in topical sections on inductive inference, teaching and PAC learning, statistical learning theory and classification, relations between models and data, bandit problems, online prediction of individual sequences, and other models of online learning.
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Inhalt
inductive inference.- teaching and PAC learning.- statistical learning theory and classification.- relations between models and data.- bandit problems, online prediction of individual sequences.- other models of online learning.
Weitere Informationen
- Allgemeine Informationen
- GTIN 09783642341052
- Editor Nader H. Bshouty, Thomas Zeugmann, Nicolas Vayatis, Gilles Stoltz
- Sprache Englisch
- Auflage 2012
- Größe H235mm x B155mm x T22mm
- Jahr 2012
- EAN 9783642341052
- Format Kartonierter Einband
- ISBN 3642341055
- Veröffentlichung 15.09.2012
- Titel Algorithmic Learning Theory
- Untertitel 23rd International Conference, ALT 2012, Lyon, France, October 29-31, 2012, Proceedings
- Gewicht 598g
- Herausgeber Springer Berlin Heidelberg
- Anzahl Seiten 396
- Lesemotiv Verstehen
- Genre Informatik