An edition of Algorithmic Learning Theory (2013)

Algorithmic Learning Theory

24th International Conference, ALT 2013, Singapore, October 6-9, 2013, Proceedings

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Last edited by MARC Bot
September 23, 2024 | History
An edition of Algorithmic Learning Theory (2013)

Algorithmic Learning Theory

24th International Conference, ALT 2013, Singapore, October 6-9, 2013, Proceedings

This book constitutes the proceedings of the 24th International Conference on Algorithmic Learning Theory, ALT 2013, held in Singapore in October 2013, and co-located with the 16th International Conference on Discovery Science, DS 2013. The 23 papers presented in this volume were carefully reviewed and selected from 39 submissions. In addition the book contains 3 full papers of invited talks. The papers are organized in topical sections named: online learning, inductive inference and grammatical inference, teaching and learning from queries, bandit theory, statistical learning theory, Bayesian/stochastic learning, and unsupervised/semi-supervised learning.

Publish Date
Publisher
Springer
Pages
415

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Book Details


Edition Notes

Source title: Algorithmic Learning Theory: 24th International Conference, ALT 2013, Singapore, October 6-9, 2013, Proceedings (Lecture Notes in Computer Science (8139))

Classifications

Library of Congress
QA75.5-76.95, Q334-342, TJ210.2-211.495

The Physical Object

Format
paperback
Number of pages
415

Edition Identifiers

Open Library
OL28158143M
ISBN 10
3642409342
ISBN 13
9783642409349

Work Identifiers

Work ID
OL20719189W

Work Description

This book constitutes the proceedings of the 25th International Conference on Algorithmic Learning Theory, ALT 2014, held in Bled, Slovenia, in October 2014, and co-located with the 17th International Conference on Discovery Science, DS 2014. The 21 papers presented in this volume were carefully reviewed and selected from 50 submissions. In addition the book contains 4 full papers summarizing the invited talks. The papers are organized in topical sections named: inductive inference; exact learning from queries; reinforcement learning; online learning and learning with bandit information; statistical learning theory; privacy, clustering, MDL, and Kolmogorov complexity.

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