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Algorithmic Learning Theory [electronic resource] : 23rd International Conference, ALT 2012, Lyon, France, October 29-31, 2012, Proceedings /

Contributor(s): Material type: TextTextSeries: Lecture Notes in Artificial Intelligence ; 7568Publisher: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2012Edition: 1st ed. 2012Description: XII, 381 p. 23 illus. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783642341069
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 -- teaching and PAC learning -- statistical learning theory and classification -- relations between models and data -- bandit problems, online prediction of individual sequences.- other models of online learning.
In: Springer Nature eBookSummary: This book constitutes the refereed proceedings of the 23rd International Conference on Algorithmic Learning Theory, ALT 2012, held in Lyon, France, in October 2012. The conference was co-located and held in parallel with the 15th International Conference on Discovery Science, DS 2012. The 23 full papers and 5 invited talks presented were carefully reviewed and selected from 47 submissions. The papers are organized in topical sections on inductive inference, teaching and PAC learning, statistical learning theory and classification, relations between models and data, bandit problems, online prediction of individual sequences, and other models of online learning.
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inductive inference -- teaching and PAC learning -- statistical learning theory and classification -- relations between models and data -- bandit problems, online prediction of individual sequences.- other models of online learning.

This book constitutes the refereed proceedings of the 23rd International Conference on Algorithmic Learning Theory, ALT 2012, held in Lyon, France, in October 2012. The conference was co-located and held in parallel with the 15th International Conference on Discovery Science, DS 2012. The 23 full papers and 5 invited talks presented were carefully reviewed and selected from 47 submissions. The papers are organized in topical sections on inductive inference, teaching and PAC learning, statistical learning theory and classification, relations between models and data, bandit problems, online prediction of individual sequences, and other models of online learning.

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