Overview
Part of the book series: Lecture Notes in Computer Science (LNCS, volume 9355)
Part of the book sub series: Lecture Notes in Artificial Intelligence (LNAI)
Included in the following conference series:
Conference proceedings info: ALT 2015.
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Table of contents (25 papers)
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Front Matter
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Inductive Inference
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Front Matter
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Learning from Queries, Teaching Complexity
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Front Matter
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Computational Learning Theory and Algorithms
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Front Matter
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Statistical Learning Theory and Sample Complexity
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Front Matter
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Other volumes
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Algorithmic Learning Theory
Keywords
- Active learning
- Boolean function learning
- Inductive inference
- Machine learning theory
- Markov Decision Processes
- Models of learning
- Online learning theory
- Query learning
- Regret bounds
- Reinforcement learning
- Unsupervised learning
- sample complexity
- generalization bounds
- algorithmic learning theory
- computational complexity
- inductive inference
- Kolmogorov complexity
- semi-supervised learning
- statistical learning theory
About this book
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.
Editors and Affiliations
Bibliographic Information
Book Title: Algorithmic Learning Theory
Book Subtitle: 26th International Conference, ALT 2015, Banff, AB, Canada, October 4-6, 2015, Proceedings
Editors: Kamalika Chaudhuri, CLAUDIO GENTILE, Sandra Zilles
Series Title: Lecture Notes in Computer Science
DOI: https://doi.org/10.1007/978-3-319-24486-0
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer International Publishing Switzerland 2015
Softcover ISBN: 978-3-319-24485-3Published: 12 September 2015
eBook ISBN: 978-3-319-24486-0Published: 04 October 2015
Series ISSN: 0302-9743
Series E-ISSN: 1611-3349
Edition Number: 1
Number of Pages: XVII, 395
Number of Illustrations: 26 illustrations in colour
Topics: Artificial Intelligence, Theory of Computation, Data Mining and Knowledge Discovery, Pattern Recognition