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Algorithmic Learning Theory [electronic resource] : 26th International Conference, ALT 2015, Banff, AB, Canada, October 4-6, 2015, Proceedings /

Contributor(s): Material type: TextTextSeries: Lecture Notes in Artificial Intelligence ; 9355Publisher: Cham : Springer International Publishing : Imprint: Springer, 2015Edition: 1st ed. 2015Description: XVII, 395 p. 26 illus. in color. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783319244860
Subject(s): Additional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification:
  • 006.3 23
LOC classification:
  • Q334-342
  • TA347.A78
Online resources:
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.
In: Springer Nature eBookSummary: 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.
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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.

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.

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