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.
By: Bshouty, Nader H [editor.].
Contributor(s): Stoltz, Gilles [editor.] | Vayatis, Nicolas [editor.] | Zeugmann, Thomas [editor.] | SpringerLink (Online service).
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BookSeries: Lecture Notes in Computer Science: 7568Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2012Description: XII, 381 p. 23 illus. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783642341069.Subject(s): Computer science | Computer software | Logic design | Artificial intelligence | Optical pattern recognition | 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 | Pattern RecognitionDDC classification: 006.3 Online resources: Click here to access online 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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