Algorithmic Learning Theory
Subtitle: 23rd International Conference, ALT 2012, Lyon, France, October 29-31, 2012. Proceedings
By: edited by Nader H. Bshouty, Gilles Stoltz, Nicolas Vayatis, Thomas Zeugmann
Contributors: Stoltz, Gilles; Vayatis, Nicolas; Zeugmann, Thomas; SpringerLink (Online service)
Series: Lecture Notes in Computer Science -- 7568
Publisher: Springer Berlin Heidelberg; Imprint: Springer
Published: 2012
Place of publication: Berlin, Heidelberg
Language: eng
Format: [electronic resource] :
Number of pages: 381
ISBN-13: 9783642341069
Subjects: Mathematical Logic and Formal Languages; Pattern perception; Optical pattern recognition; Computer science; Algorithm Analysis and Problem Complexity; Logic design; Logics and Meanings of Programs; Computation by Abstract Devices; Artificial Intelligence (incl. Robotics); Artificial intelligence; Computer software
Description: 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.
Table of contents: title: inductive inference; title: teaching and PAC learning; title: statistical learning theory and classification; title: relations between models and data; title: bandit problems, online prediction of individual sequences.- other models of online learning.