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Algorithmic Learning Theory

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Algorithmic Learning Theory Synopsis

This book constitutes the proceedings of the 26th International Conference on Algorithmic Learning Theory, ALT 2015, held in Banff, AB, Canada, in October 2015, and co-located with the 18th International Conference on Discovery Science, DS 2015. The 23 full papers presented in this volume were carefully reviewed and selected from 44 submissions. In addition the book contains 2 full papers summarizing the invited talks and 2 abstracts of invited talks. The papers are organized in topical sections named: inductive inference; learning from queries, teaching complexity; computational learning theory and algorithms; statistical learning theory and sample complexity; online learning, stochastic optimization; and Kolmogorov complexity, algorithmic information theory.

About This Edition

ISBN: 9783319244853
Publication date: 12th September 2015
Author: Kamalika Chaudhuri
Publisher: Springer International Publishing AG
Format: Paperback
Pagination: 395 pages
Series: Lecture Notes in Artificial Intelligence
Genres: Artificial intelligence
Mathematical theory of computation
Data mining
Expert systems / knowledge-based systems
Pattern recognition