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Algorithmic Learning Theory [electronic resource] : 23rd International Conference, ALT 2012, Lyon, France, October 29-31, 2012, Proceedings / edited by Nader H. Bshouty, Gilles Stoltz, Nicolas Vayatis, Thomas Zeugmann.

Contributor(s): Bshouty, Nader H [editor.] | Stoltz, Gilles [editor.] | Vayatis, Nicolas [editor.] | Zeugmann, Thomas [editor.] | SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Lecture Notes in Artificial Intelligence: 7568Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2012Edition: 1st ed. 2012.Description: XII, 381 p. 23 illus. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783642341069.Subject(s): Artificial intelligence | Machine theory | Algorithms | Computer science | Pattern recognition systems | Artificial Intelligence | Formal Languages and Automata Theory | Algorithms | Theory of Computation | Computer Science Logic and Foundations of Programming | Automated Pattern RecognitionAdditional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification: 006.3 Online resources: Click here to access online
Contents:
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.
In: Springer Nature eBookSummary: 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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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.

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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