Algorithmic Learning Theory : 26th International Conference, ALT 2015, Banff, AB, Canada, October 4-6, 2015, Proceedings

Kamalika Chaudhuri

ISBN 10: 331924485X / ISBN 13: 9783319244853

Editore: Springer International Publishing, Springer International Publishing, 2015

Riguardo questo articolo

Druck auf Anfrage Neuware - Printed after ordering - 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.

Codice articolo 9783319244853

Dati bibliografici

• Titolo: Algorithmic Learning Theory : 26th International Conference, ALT 2015, Banff, AB, Canada, October 4-6, 2015, Proceedings
• Editore: Springer International Publishing, Springer International Publishing
• Data di pubblicazione: 2015
• Lingua: Inglese
• ISBN 10: 331924485X
• ISBN 13: 9783319244853
• Rilegatura: Taschenbuch
• Condizione: Neu
• Dimensioni: 235 L x 155 A x 23 P (millimetri) 235 millimetri di larghezza per 155 millimetri di altezza per 23 millimetri di profondità
• Peso: 628 grammi

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Riassunto

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.