By Ronald Ortner, Hans Ulrich Simon, Sandra Zilles

ISBN-10: 3319463780

ISBN-13: 9783319463780

ISBN-10: 3319463799

ISBN-13: 9783319463797

This ebook constitutes the refereed court cases of the twenty seventh overseas convention on Algorithmic studying thought, ALT 2016, held in Bari, Italy, in October 2016, co-located with the nineteenth foreign convention on Discovery technological know-how, DS 2016. The 24 commonplace papers awarded during this quantity have been conscientiously reviewed and chosen from forty five submissions. moreover the booklet includes five abstracts of invited talks. The papers are geared up in topical sections named: mistakes bounds, pattern compression schemes; statistical studying, idea, evolvability; certain and interactive studying; complexity of educating types; inductive inference; on-line studying; bandits and reinforcement studying; and clustering.

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Additional resources for Algorithmic Learning Theory: 27th International Conference, ALT 2016, Bari, Italy, October 19-21, 2016, Proceedings

Example text

Finally, in Sect. 4 we relate unlabeled compression schemes for extremal classes with basic open questions concerning extremal classes. 1 37 Extremal Classes Preliminaries Concepts, Concept Classes, and the One-Inclusion Graph. A concept c is a mapping from some domain to {0, 1}. We assume that the domain of c (denoted by dom(c)) is finite and allow the case that dom(c) = ∅. e. for any domain point x ∈ dom(c), c(x) = 1 iff x ∈ c. A concept class C is a set of concepts with the same domain (denoted by dom(C)).

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Stat. 34(6), 2593–2656 (2006) 13. : Convergence of estimates under dimensionality restrictions. Ann. Statist. 1, 38–53 (1973) 14. : Oracle inequalities for cross-validation type procedures. Electron. J. Stat. 6, 1803–1837 (2012) 15. : Learning subgaussian classes: upper and minimax bounds (2013). 4825 16. : Learning with square loss: localization through offset Rademacher complexity. In: Proceedings of The 28th Conference on Learning Theory (2015) 17. : Concentration Inequalties and Model Selection.

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Algorithmic Learning Theory: 27th International Conference, ALT 2016, Bari, Italy, October 19-21, 2016, Proceedings by Ronald Ortner, Hans Ulrich Simon, Sandra Zilles

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