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Algorithmic Learning Theory : 26th International Conference, ALT 2015, Banff, AB, Canada, October 4-6, 2015, Proceedings / edited by Kamalika Chaudhuri, CLAUDIO GENTILE, Sandra Zilles.
- Format:
- Book
- Series:
- Computer Science (SpringerNature-11645)
- Lecture notes in computer science. Lecture notes in artificial intelligence 2945-9141 ; 9355
- Lecture Notes in Artificial Intelligence, 2945-9141 ; 9355
- Language:
- English
- Subjects (All):
- Artificial intelligence.
- Computer science.
- Data mining.
- Pattern recognition systems.
- Artificial Intelligence.
- Theory of Computation.
- Data Mining and Knowledge Discovery.
- Automated Pattern Recognition.
- Local Subjects:
- Artificial Intelligence.
- Theory of Computation.
- Data Mining and Knowledge Discovery.
- Automated Pattern Recognition.
- Physical Description:
- 1 online resource (XVII, 395 pages) : 26 illustrations in color.
- Edition:
- 1st ed. 2015.
- Contained In:
- Springer Nature eBook
- Place of Publication:
- Cham : Springer International Publishing : Imprint: Springer, 2015.
- System Details:
- text file PDF
- Summary:
- 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.
- Contents:
- Inductive inference
- Learning from queries, teaching complexity
- Computational learning theory and algorithms
- Statistical learning theory and sample complexity
- Online learning
- Stochastic optimization
- Kolmogorov complexity, algorithmic information theory.
- Other Format:
- Printed edition:
- ISBN:
- 978-3-319-24486-0
- 9783319244860
- Access Restriction:
- Restricted for use by site license.
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