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» On learning with dissimilarity functions
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ICPR
2006
IEEE
16 years 7 months ago
Exploiting the Geometry of Gene Expression Patterns for Unsupervised Learning
Typical gene expression clustering algorithms are restricted to a specific underlying pattern model while overlooking the possibility that other information carrying patterns may ...
Rave Harpaz, Robert M. Haralick
ADBIS
2005
Springer
100views Database» more  ADBIS 2005»
16 years 6 days ago
Evolutionary Learning of Boolean Queries by Genetic Programming
Abstract. The performance of an information retrieval system is usually measured in terms of two different criteria, precision and recall. This way, the optimization of any of its...
Suhail S. J. Owais, Pavel Krömer, Václ...
ICA
2004
Springer
16 years 1 days ago
Post-nonlinear Independent Component Analysis by Variational Bayesian Learning
Post-nonlinear (PNL) independent component analysis (ICA) is a generalisation of ICA where the observations are assumed to have been generated from independent sources by linear mi...
Alexander Ilin, Antti Honkela
EUSFLAT
2003
115views Fuzzy Logic» more  EUSFLAT 2003»
15 years 8 months ago
A hierarchical fuzzy rule-based learning system based on an information theoretic
This paper proposes a new novel method for the online construction of a Hierarchical Fuzzy Rule Based System (FRBS) to accurately model a function while retaining a level of human...
Antony Waldock, Brian Carse, Chris Melhuish
SDM
2004
SIAM
218views Data Mining» more  SDM 2004»
15 years 8 months ago
Mixture Density Mercer Kernels: A Method to Learn Kernels Directly from Data
This paper presents a method of generating Mercer Kernels from an ensemble of probabilistic mixture models, where each mixture model is generated from a Bayesian mixture density e...
Ashok N. Srivastava