Algorithmic Learning Theory
27th International Conference, ALT 2016, Bari, Italy, October 19-21, 2016, Proceedings
(Sprache: Englisch)
This book constitutes the refereed proceedings of the 27th International Conference on Algorithmic Learning Theory, ALT 2016, held in Bari, Italy, in October 2016, co-located with the 19th International Conference on Discovery Science, DS 2016. The 24...
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This book constitutes the refereed proceedings of the 27th International Conference on Algorithmic Learning Theory, ALT 2016, held in Bari, Italy, in October 2016, co-located with the 19th International Conference on Discovery Science, DS 2016. The 24 regular papers presented in this volume were carefully reviewed and selected from 45 submissions. In addition the book contains 5 abstracts of invited talks. The papers are organized in topical sections named: error bounds, sample compression schemes; statistical learning, theory, evolvability; exact and interactive learning; complexity of teaching models; inductive inference; online learning; bandits and reinforcement learning; and clustering.Inhaltsverzeichnis zu „Algorithmic Learning Theory “
Error bounds, sample compression schemes.- Statistical learning, theory, evolvability.- Exact and interactive learning.- Complexity of teaching models.- Inductive inference.- Online learning.- Bandits and reinforcement learning.- Clustering.Bibliographische Angaben
- 2016, 1st ed. 2016, XIX, 371 Seiten, Maße: 15,5 x 23,5 cm, Kartoniert (TB), Englisch
- Herausgegeben: Ronald Ortner, Hans Ulrich Simon, Sandra Zilles
- Verlag: Springer, Berlin
- ISBN-10: 3319463780
- ISBN-13: 9783319463780
- Erscheinungsdatum: 21.09.2016
Sprache:
Englisch
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