Algorithmic Learning Theory [electronic resource] : 22nd International Conference, ALT 2011, Espoo, Finland, October 5-7, 2011, Proceedings / edited by Jyriki Kivinen, Csaba Szepesvári, Esko Ukkonen, Thomas Zeugmann.
Contributor(s): Kivinen, Jyriki [editor.] | Szepesvári, Csaba [editor.] | Ukkonen, Esko [editor.] | Zeugmann, Thomas [editor.] | SpringerLink (Online service).
Material type: BookSeries: Lecture Notes in Artificial Intelligence: 6925Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2011Edition: 1st ed. 2011.Description: XIII, 453 p. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783642244124.Subject(s): Artificial intelligence | Machine theory | Algorithms | Computer science | Application software | Artificial Intelligence | Formal Languages and Automata Theory | Algorithms | Theory of Computation | Computer Science Logic and Foundations of Programming | Computer and Information Systems ApplicationsAdditional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification: 006.3 Online resources: Click here to access online In: Springer Nature eBookSummary: This book constitutes the refereed proceedings of the 22nd International Conference on Algorithmic Learning Theory, ALT 2011, held in Espoo, Finland, in October 2011, co-located with the 14th International Conference on Discovery Science, DS 2011. The 28 revised full papers presented together with the abstracts of 5 invited talks were carefully reviewed and selected from numerous submissions. The papers are divided into topical sections of papers on inductive inference, regression, bandit problems, online learning, kernel and margin-based methods, intelligent agents and other learning models.This book constitutes the refereed proceedings of the 22nd International Conference on Algorithmic Learning Theory, ALT 2011, held in Espoo, Finland, in October 2011, co-located with the 14th International Conference on Discovery Science, DS 2011. The 28 revised full papers presented together with the abstracts of 5 invited talks were carefully reviewed and selected from numerous submissions. The papers are divided into topical sections of papers on inductive inference, regression, bandit problems, online learning, kernel and margin-based methods, intelligent agents and other learning models.
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