Lecture Notes in Computer Science - Deterministic and Statistical Methods in Machine Learning
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Published By Springer Berlin Heidelberg

9783540290735, 9783540317289

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Transformations of Gaussian Process Priors

Lecture Notes in Computer Science - Deterministic and Statistical Methods in Machine Learning ◽

10.1007/11559887_7 ◽

2005 ◽

pp. 110-123 ◽

Cited By ~ 12

Author(s):

Roderick Murray-Smith ◽

Barak A. Pearlmutter

Keyword(s):

Gaussian Process

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Extensions of the Informative Vector Machine

Lecture Notes in Computer Science - Deterministic and Statistical Methods in Machine Learning ◽

10.1007/11559887_4 ◽

2005 ◽

pp. 56-87 ◽

Cited By ~ 14

Author(s):

Neil D. Lawrence ◽

John C. Platt ◽

Michael I. Jordan

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Guiding Local Regression Using Visualisation

Lecture Notes in Computer Science - Deterministic and Statistical Methods in Machine Learning ◽

10.1007/11559887_6 ◽

2005 ◽

pp. 98-109

Author(s):

Dharmesh M. Maniyar ◽

Ian T. Nabney

Keyword(s):

Local Regression

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Appropriate Kernel Functions for Support Vector Machine Learning with Sequences of Symbolic Data

Lecture Notes in Computer Science - Deterministic and Statistical Methods in Machine Learning ◽

10.1007/11559887_16 ◽

2005 ◽

pp. 256-280 ◽

Cited By ~ 12

Author(s):

Bram Vanschoenwinkel ◽

Bernard Manderick

Keyword(s):

Machine Learning ◽

Support Vector Machine ◽

Kernel Functions ◽

Support Vector ◽

Symbolic Data

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Variational Bayes Estimation of Mixing Coefficients

Lecture Notes in Computer Science - Deterministic and Statistical Methods in Machine Learning ◽

10.1007/11559887_17 ◽

2005 ◽

pp. 281-295 ◽

Cited By ~ 5

Author(s):

Bo Wang ◽

D. M. Titterington

Keyword(s):

Variational Bayes ◽

Bayes Estimation ◽

Mixing Coefficients

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Object Recognition via Local Patch Labelling

Lecture Notes in Computer Science - Deterministic and Statistical Methods in Machine Learning ◽

10.1007/11559887_1 ◽

2005 ◽

pp. 1-21 ◽

Cited By ~ 9

Author(s):

Christopher M. Bishop ◽

Ilkay Ulusoy

Keyword(s):

Object Recognition ◽

Local Patch

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Bayesian Independent Component Analysis with Prior Constraints: An Application in Biosignal Analysis

Lecture Notes in Computer Science - Deterministic and Statistical Methods in Machine Learning ◽

10.1007/11559887_10 ◽

2005 ◽

pp. 159-179 ◽

Cited By ~ 5

Author(s):

Stephen Roberts ◽

Rizwan Choudrey

Keyword(s):

Independent Component Analysis ◽

Component Analysis ◽

Independent Component ◽

Biosignal Analysis

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Redundant Bit Vectors for Quickly Searching High-Dimensional Regions

Lecture Notes in Computer Science - Deterministic and Statistical Methods in Machine Learning ◽

10.1007/11559887_9 ◽

2005 ◽

pp. 137-158 ◽

Cited By ~ 10

Author(s):

Jonathan Goldstein ◽

John C. Plat ◽

Christopher J. C. Burges

Keyword(s):

High Dimensional

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Understanding Gaussian Process Regression Using the Equivalent Kernel

Lecture Notes in Computer Science - Deterministic and Statistical Methods in Machine Learning ◽

10.1007/11559887_13 ◽

2005 ◽

pp. 211-228 ◽

Cited By ~ 13

Author(s):

Peter Sollich ◽

Christopher K. I. Williams

Keyword(s):

Gaussian Process ◽

Gaussian Process Regression

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SVM Based Learning System for Information Extraction

Lecture Notes in Computer Science - Deterministic and Statistical Methods in Machine Learning ◽

10.1007/11559887_19 ◽

2005 ◽

pp. 319-339 ◽

Cited By ~ 30

Author(s):

Yaoyong Li ◽

Kalina Bontcheva ◽

Hamish Cunningham

Keyword(s):

Information Extraction ◽

Learning System

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Lecture Notes in Computer Science - Deterministic and Statistical Methods in Machine LearningLatest Publications

TOTAL DOCUMENTS

H-INDEX

Published By Springer Berlin Heidelberg

Transformations of Gaussian Process Priors

Extensions of the Informative Vector Machine

Guiding Local Regression Using Visualisation

Appropriate Kernel Functions for Support Vector Machine Learning with Sequences of Symbolic Data

Variational Bayes Estimation of Mixing Coefficients

Object Recognition via Local Patch Labelling

Bayesian Independent Component Analysis with Prior Constraints: An Application in Biosignal Analysis

Redundant Bit Vectors for Quickly Searching High-Dimensional Regions

Understanding Gaussian Process Regression Using the Equivalent Kernel

SVM Based Learning System for Information Extraction

Lecture Notes in Computer Science - Deterministic and Statistical Methods in Machine Learning
Latest Publications