Algorithmic Learning Theory [electronic resource] : 22nd International Conference, ALT 2011, Espoo, Finland, October 5-7, 2011. Proceedings / edited by Jyrki Kivinen, Csaba Szepesvári, Esko Ukkonen, Thomas Zeugmann.
By: Kivinen, Jyrki [editor.].
Contributor(s): Szepesvári, Csaba [editor.] | Ukkonen, Esko [editor.] | Zeugmann, Thomas [editor.] | SpringerLink (Online service).
Material type:
BookSeries: Lecture Notes in Computer Science: 6925Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg, 2011Description: XIII, 453 p. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783642244124.Subject(s): Computer science | Computer software | Logic design | Artificial intelligence | Computer Science | Artificial Intelligence (incl. Robotics) | Mathematical Logic and Formal Languages | Algorithm Analysis and Problem Complexity | Computation by Abstract Devices | Logics and Meanings of Programs | Information Systems Applications (incl. Internet)DDC classification: 006.3 Online resources: Click here to access online
In:
Springer eBooksSummary: 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.
There are no comments for this item.