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Algorithmic Learning Theory

  • Kartonierter Einband
  • 392 Seiten
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This book constitutes the refereed proceedings of the 27th International Conference on Algorithmic Learning Theory, ALT 2016, held... Weiterlesen
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Beschreibung

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.



Inhalt

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.

Produktinformationen

Titel: Algorithmic Learning Theory
Untertitel: 27th International Conference, ALT 2016, Bari, Italy, October 19-21, 2016, Proceedings
Editor:
EAN: 9783319463780
ISBN: 3319463780
Format: Kartonierter Einband
Herausgeber: Springer International Publishing
Genre: Anwendungs-Software
Anzahl Seiten: 392
Gewicht: 593g
Größe: H235mm x B155mm x T21mm
Jahr: 2016
Untertitel: Englisch
Auflage: 1st ed. 2016

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