Perspectives in Neural Computing - An Information-Theoretic Approach to Neural Computing
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Published By Springer New York

9781461284697, 9781461240167

Latest Documents Most Cited Documents Contributed Authors Related Sources Related Keywords

Nonlinear Feature Extraction: Boolean Stochastic Networks

Perspectives in Neural Computing - An Information-Theoretic Approach to Neural Computing ◽

10.1007/978-1-4612-4016-7_5 ◽

1996 ◽

pp. 109-133

Author(s):

Gustavo Deco ◽

Dragan Obradovic

Keyword(s):

Feature Extraction ◽

Stochastic Networks ◽

Nonlinear Feature Extraction ◽

Nonlinear Feature

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Linear Feature Extraction: Infomax Principle

Perspectives in Neural Computing - An Information-Theoretic Approach to Neural Computing ◽

10.1007/978-1-4612-4016-7_3 ◽

1996 ◽

pp. 41-63

Author(s):

Gustavo Deco ◽

Dragan Obradovic

Keyword(s):

Feature Extraction ◽

Linear Feature ◽

Linear Feature Extraction

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Preliminaries of Information Theory and Neural Networks

Perspectives in Neural Computing - An Information-Theoretic Approach to Neural Computing ◽

10.1007/978-1-4612-4016-7_2 ◽

1996 ◽

pp. 7-37

Author(s):

Gustavo Deco ◽

Dragan Obradovic

Keyword(s):

Neural Networks ◽

Information Theory

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Statistical Physics Theory of Supervised Learning and Generalization

Perspectives in Neural Computing - An Information-Theoretic Approach to Neural Computing ◽

10.1007/978-1-4612-4016-7_8 ◽

1996 ◽

pp. 187-217

Author(s):

Gustavo Deco ◽

Dragan Obradovic

Keyword(s):

Supervised Learning ◽

Statistical Physics

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Nonlinear Feature Extraction: Deterministic Neural Networks

Perspectives in Neural Computing - An Information-Theoretic Approach to Neural Computing ◽

10.1007/978-1-4612-4016-7_6 ◽

1996 ◽

pp. 135-166

Author(s):

Gustavo Deco ◽

Dragan Obradovic

Keyword(s):

Neural Networks ◽

Feature Extraction ◽

Nonlinear Feature Extraction ◽

Nonlinear Feature

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Supervised Learning and Statistical Estimation

Perspectives in Neural Computing - An Information-Theoretic Approach to Neural Computing ◽

10.1007/978-1-4612-4016-7_7 ◽

1996 ◽

pp. 169-186

Author(s):

Gustavo Deco ◽

Dragan Obradovic

Keyword(s):

Supervised Learning ◽

Statistical Estimation

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Composite Networks

Perspectives in Neural Computing - An Information-Theoretic Approach to Neural Computing ◽

10.1007/978-1-4612-4016-7_9 ◽

1996 ◽

pp. 219-224 ◽

Cited By ~ 1

Author(s):

Gustavo Deco ◽

Dragan Obradovic

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Independent Component Analysis: General Formulation and Linear Case

Perspectives in Neural Computing - An Information-Theoretic Approach to Neural Computing ◽

10.1007/978-1-4612-4016-7_4 ◽

1996 ◽

pp. 65-107 ◽

Cited By ~ 1

Author(s):

Gustavo Deco ◽

Dragan Obradovic

Keyword(s):

Independent Component Analysis ◽

Component Analysis ◽

Independent Component ◽

Linear Case

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Information Theory Based Regularizing Methods

Perspectives in Neural Computing - An Information-Theoretic Approach to Neural Computing ◽

10.1007/978-1-4612-4016-7_10 ◽

1996 ◽

pp. 225-241

Author(s):

Gustavo Deco ◽

Dragan Obradovic

Keyword(s):

Information Theory

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Introduction

Perspectives in Neural Computing - An Information-Theoretic Approach to Neural Computing ◽

10.1007/978-1-4612-4016-7_1 ◽

1996 ◽

pp. 1-5 ◽

Cited By ~ 1

Author(s):

Gustavo Deco ◽

Dragan Obradovic

Download Full-text

Perspectives in Neural Computing - An Information-Theoretic Approach to Neural ComputingLatest Publications

TOTAL DOCUMENTS

H-INDEX

Published By Springer New York

Nonlinear Feature Extraction: Boolean Stochastic Networks

Linear Feature Extraction: Infomax Principle

Preliminaries of Information Theory and Neural Networks

Statistical Physics Theory of Supervised Learning and Generalization

Nonlinear Feature Extraction: Deterministic Neural Networks

Supervised Learning and Statistical Estimation

Composite Networks

Independent Component Analysis: General Formulation and Linear Case

Information Theory Based Regularizing Methods

Introduction

Perspectives in Neural Computing - An Information-Theoretic Approach to Neural Computing
Latest Publications