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

9783540591191, 9783540491958

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Learnability of Kolmogorov-easy circuit expressions via queries

Lecture Notes in Computer Science - Computational Learning Theory ◽

10.1007/3-540-59119-2_172 ◽

1995 ◽

pp. 112-124

Author(s):

José L. Balcázar ◽

Harry Buhrman ◽

Montserrat Hermo

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Is pocket algorithm optimal?

Lecture Notes in Computer Science - Computational Learning Theory ◽

10.1007/3-540-59119-2_185 ◽

1995 ◽

pp. 287-297

Author(s):

Marco Muselli

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The query complexity of learning some subclasses of context-free grammars

Lecture Notes in Computer Science - Computational Learning Theory ◽

10.1007/3-540-59119-2_195 ◽

1995 ◽

pp. 404-414 ◽

Cited By ~ 1

Author(s):

Carlos Domingo ◽

Víctor Lavín

Keyword(s):

Query Complexity ◽

Context Free ◽

Context Free Grammars

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Learning by extended statistical queries and its relation to PAC learning

Lecture Notes in Computer Science - Computational Learning Theory ◽

10.1007/3-540-59119-2_191 ◽

1995 ◽

pp. 357-366 ◽

Cited By ~ 4

Author(s):

Eli Shamir ◽

Clara Shwartzman

Keyword(s):

Pac Learning ◽

Statistical Queries

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Some theorems concerning the free energy of (Un) constrained stochastic Hopfield neural networks

Lecture Notes in Computer Science - Computational Learning Theory ◽

10.1007/3-540-59119-2_186 ◽

1995 ◽

pp. 298-312 ◽

Cited By ~ 1

Author(s):

Jan Berg ◽

Jan C. Bioch

Keyword(s):

Neural Networks ◽

Free Energy ◽

Hopfield Neural Networks

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MDL learning of unions of simple pattern languages from positive examples

Lecture Notes in Computer Science - Computational Learning Theory ◽

10.1007/3-540-59119-2_182 ◽

1995 ◽

pp. 252-260 ◽

Cited By ~ 7

Author(s):

Pekka Kilpeläinen ◽

Heikki Mannila ◽

Esko Ukkonen

Keyword(s):

Simple Pattern ◽

Pattern Languages

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On-line maximum likelihood prediction with respect to general loss functions

Lecture Notes in Computer Science - Computational Learning Theory ◽

10.1007/3-540-59119-2_170 ◽

1995 ◽

pp. 84-98

Author(s):

Kenji Yamanishi

Keyword(s):

Maximum Likelihood ◽

Loss Functions ◽

On Line ◽

General Loss Functions ◽

Maximum Likelihood Prediction

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Learning decision lists and trees with equivalence-queries

Lecture Notes in Computer Science - Computational Learning Theory ◽

10.1007/3-540-59119-2_188 ◽

1995 ◽

pp. 322-336 ◽

Cited By ~ 11

Author(s):

Hans Ulrich Simon

Keyword(s):

Decision Lists ◽

Equivalence Queries

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The discovery of algorithmic probability: A guide for the programming of true creativity

Lecture Notes in Computer Science - Computational Learning Theory ◽

10.1007/3-540-59119-2_165 ◽

1995 ◽

pp. 1-22 ◽

Cited By ~ 1

Author(s):

Ray J. Solomonoff

Keyword(s):

Algorithmic Probability

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A note on the use of probabilities by mechanical learners

Lecture Notes in Computer Science - Computational Learning Theory ◽

10.1007/3-540-59119-2_183 ◽

1995 ◽

pp. 261-271

Author(s):

Eric Martin ◽

Daniel Osherson

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Lecture Notes in Computer Science - Computational Learning TheoryLatest Publications

TOTAL DOCUMENTS

H-INDEX

Published By Springer Berlin Heidelberg

Learnability of Kolmogorov-easy circuit expressions via queries

Is pocket algorithm optimal?

The query complexity of learning some subclasses of context-free grammars

Learning by extended statistical queries and its relation to PAC learning

Some theorems concerning the free energy of (Un) constrained stochastic Hopfield neural networks

MDL learning of unions of simple pattern languages from positive examples

On-line maximum likelihood prediction with respect to general loss functions

Learning decision lists and trees with equivalence-queries

The discovery of algorithmic probability: A guide for the programming of true creativity

A note on the use of probabilities by mechanical learners

Lecture Notes in Computer Science - Computational Learning Theory
Latest Publications