Lecture Notes in Computer Science - Algorithmic Learning Theory
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Published By Springer Berlin Heidelberg

9783642341052, 9783642341069

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Enlarging Learnable Classes

Lecture Notes in Computer Science - Algorithmic Learning Theory ◽

10.1007/978-3-642-34106-9_7 ◽

2012 ◽

pp. 36-50

Author(s):

Sanjay Jain ◽

Timo Kötzing ◽

Frank Stephan

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Buy Low, Sell High

Lecture Notes in Computer Science - Algorithmic Learning Theory ◽

10.1007/978-3-642-34106-9_27 ◽

2012 ◽

pp. 335-349 ◽

Cited By ~ 3

Author(s):

Wouter M. Koolen ◽

Vladimir Vovk

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The Safe Bayesian

Lecture Notes in Computer Science - Algorithmic Learning Theory ◽

10.1007/978-3-642-34106-9_16 ◽

2012 ◽

pp. 169-183 ◽

Cited By ~ 10

Author(s):

Peter Grünwald

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Regular Inference as Vertex Coloring

Lecture Notes in Computer Science - Algorithmic Learning Theory ◽

10.1007/978-3-642-34106-9_10 ◽

2012 ◽

pp. 81-95 ◽

Cited By ~ 2

Author(s):

Christophe Costa Florêncio ◽

Sicco Verwer

Keyword(s):

Vertex Coloring

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On the Learnability of Shuffle Ideals

Lecture Notes in Computer Science - Algorithmic Learning Theory ◽

10.1007/978-3-642-34106-9_12 ◽

2012 ◽

pp. 111-123 ◽

Cited By ~ 1

Author(s):

Dana Angluin ◽

James Aspnes ◽

Aryeh Kontorovich

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Predictive Complexity and Generalized Entropy Rate of Stationary Ergodic Processes

Lecture Notes in Computer Science - Algorithmic Learning Theory ◽

10.1007/978-3-642-34106-9_29 ◽

2012 ◽

pp. 365-379 ◽

Cited By ~ 2

Author(s):

Mrinalkanti Ghosh ◽

Satyadev Nandakumar

Keyword(s):

Entropy Rate ◽

Generalized Entropy ◽

Ergodic Processes

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Weighted Last-Step Min-Max Algorithm with Improved Sub-logarithmic Regret

Lecture Notes in Computer Science - Algorithmic Learning Theory ◽

10.1007/978-3-642-34106-9_21 ◽

2012 ◽

pp. 245-259

Author(s):

Edward Moroshko ◽

Koby Crammer

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Regret Bounds for Restless Markov Bandits

Lecture Notes in Computer Science - Algorithmic Learning Theory ◽

10.1007/978-3-642-34106-9_19 ◽

2012 ◽

pp. 214-228 ◽

Cited By ~ 7

Author(s):

Ronald Ortner ◽

Daniil Ryabko ◽

Peter Auer ◽

Rémi Munos

Keyword(s):

Regret Bounds

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Data Stability in Clustering: A Closer Look

Lecture Notes in Computer Science - Algorithmic Learning Theory ◽

10.1007/978-3-642-34106-9_17 ◽

2012 ◽

pp. 184-198 ◽

Cited By ~ 3

Author(s):

Lev Reyzin

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Learnability beyond Uniform Convergence

Lecture Notes in Computer Science - Algorithmic Learning Theory ◽

10.1007/978-3-642-34106-9_3 ◽

2012 ◽

pp. 13-16

Author(s):

Shai Shalev-Shwartz

Keyword(s):

Uniform Convergence

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Lecture Notes in Computer Science - Algorithmic Learning TheoryLatest Publications

TOTAL DOCUMENTS

H-INDEX

Published By Springer Berlin Heidelberg

Enlarging Learnable Classes

Buy Low, Sell High

The Safe Bayesian

Regular Inference as Vertex Coloring

On the Learnability of Shuffle Ideals

Predictive Complexity and Generalized Entropy Rate of Stationary Ergodic Processes

Weighted Last-Step Min-Max Algorithm with Improved Sub-logarithmic Regret

Regret Bounds for Restless Markov Bandits

Data Stability in Clustering: A Closer Look

Learnability beyond Uniform Convergence

Lecture Notes in Computer Science - Algorithmic Learning Theory
Latest Publications