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

9783540667483, 9783540467694

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Generalization Error of Linear Neural Networks in Unidentifiable Cases

Lecture Notes in Computer Science - Algorithmic Learning Theory ◽

10.1007/3-540-46769-6_5 ◽

1999 ◽

pp. 51-62 ◽

Cited By ~ 9

Author(s):

Kenji Fukumizu

Keyword(s):

Neural Networks ◽

Generalization Error

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The Consistency Dimension and Distribution-Dependent Learning from Queries (Extended Abstract)

Lecture Notes in Computer Science - Algorithmic Learning Theory ◽

10.1007/3-540-46769-6_7 ◽

1999 ◽

pp. 77-92 ◽

Cited By ~ 5

Author(s):

José L. Balcázar ◽

Jorge Castro ◽

David Guijarro ◽

Hans-Ulrich Simon

Keyword(s):

Dependent Learning

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Finding Relevant Variables in PAC Model with Membership Queries

Lecture Notes in Computer Science - Algorithmic Learning Theory ◽

10.1007/3-540-46769-6_26 ◽

1999 ◽

pp. 313-322 ◽

Cited By ~ 7

Author(s):

David Guijarro ◽

Jun Tarui ◽

Tatsuie Tsukiji

Keyword(s):

Membership Queries ◽

Relevant Variables ◽

Pac Model

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Boolean Formulas Are Hard to Learn for Most Gate Bases

Lecture Notes in Computer Science - Algorithmic Learning Theory ◽

10.1007/3-540-46769-6_25 ◽

1999 ◽

pp. 301-312

Author(s):

Víctor Dalmau

Keyword(s):

Boolean Formulas

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Complexity in the Case Against Accuracy: When Building One Function-Free Horn Clause Is as Hard as Any

Lecture Notes in Computer Science - Algorithmic Learning Theory ◽

10.1007/3-540-46769-6_15 ◽

1999 ◽

pp. 182-193

Author(s):

Richard Nock

Keyword(s):

Horn Clause

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Induction of Logic Programs Based on ψ-Terms

Lecture Notes in Computer Science - Algorithmic Learning Theory ◽

10.1007/3-540-46769-6_14 ◽

1999 ◽

pp. 169-181 ◽

Cited By ~ 1

Author(s):

Yutaka Sasaki

Keyword(s):

Logic Programs

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PAC Learning with Nasty Noise

Lecture Notes in Computer Science - Algorithmic Learning Theory ◽

10.1007/3-540-46769-6_17 ◽

1999 ◽

pp. 206-218 ◽

Cited By ~ 4

Author(s):

Nader H. Bshouty ◽

Nadav Eiron ◽

Eyal Kushilevitz

Keyword(s):

Pac Learning

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On the Uniform Learnability of Approximations to Non-recursive Functions

Lecture Notes in Computer Science - Algorithmic Learning Theory ◽

10.1007/3-540-46769-6_23 ◽

1999 ◽

pp. 276-290 ◽

Cited By ~ 2

Author(s):

Frank Stephan ◽

Thomas Zeugmann

Keyword(s):

Recursive Functions

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Inductive Learning with Corroboration

Lecture Notes in Computer Science - Algorithmic Learning Theory ◽

10.1007/3-540-46769-6_12 ◽

1999 ◽

pp. 145-156

Author(s):

Phil Watson

Keyword(s):

Inductive Learning

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Algebraic Analysis for Singular Statistical Estimation

Lecture Notes in Computer Science - Algorithmic Learning Theory ◽

10.1007/3-540-46769-6_4 ◽

1999 ◽

pp. 39-50 ◽

Cited By ~ 21

Author(s):

Sumio Watanabe

Keyword(s):

Statistical Estimation ◽

Algebraic Analysis

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Lecture Notes in Computer Science - Algorithmic Learning TheoryLatest Publications

TOTAL DOCUMENTS

H-INDEX

Published By Springer Berlin Heidelberg

Generalization Error of Linear Neural Networks in Unidentifiable Cases

The Consistency Dimension and Distribution-Dependent Learning from Queries (Extended Abstract)

Finding Relevant Variables in PAC Model with Membership Queries

Boolean Formulas Are Hard to Learn for Most Gate Bases

Complexity in the Case Against Accuracy: When Building One Function-Free Horn Clause Is as Hard as Any

Induction of Logic Programs Based on ψ-Terms

PAC Learning with Nasty Noise

On the Uniform Learnability of Approximations to Non-recursive Functions

Inductive Learning with Corroboration

Algebraic Analysis for Singular Statistical Estimation

Lecture Notes in Computer Science - Algorithmic Learning Theory
Latest Publications