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PAA
2008
15 years 6 months ago
A sparse Bayesian approach for joint feature selection and classifier learning
Abstract In this paper we present a new method for Joint Feature Selection and Classifier Learning (JFSCL) using a sparse Bayesian approach. These tasks are performed by optimizing...
Àgata Lapedriza, Santi Seguí, David ...
PRL
2006
124views more  PRL 2006»
15 years 6 months ago
Parameter selection for suppressed fuzzy c-means with an application to MRI segmentation
This paper presents an algorithm, called the modified suppressed fuzzy c-means (MS-FCM), that simultaneously performs clustering and parameter selection for the suppressed fuzzy c...
Wen-Liang Hung, Miin-Shen Yang, De-Hua Chen
COMPLEXITY
2004
165views more  COMPLEXITY 2004»
15 years 6 months ago
Sex promotes gamete selection: A quantitative comparative study of features favoring the evolution of sex
: Explaining the maintenance of sexual reproduction remains one of the greatest challenges in biology. The theoretical oddity of sex is based on at least three advantages that asex...
Klaus Jaffe
CSDA
2004
105views more  CSDA 2004»
15 years 6 months ago
Computational aspects of algorithms for variable selection in the context of principal components
Variable selection consists in identifying a k-subset of a set of original variables that is optimal for a given criterion of adequate approximation to the whole data set. Several...
Jorge Cadima, J. Orestes Cerdeira, Manuel Minhoto
BC
2000
91views more  BC 2000»
15 years 6 months ago
Computational model of dot-pattern selective cells
Abstract. A computational model of a dot-pattern selective neuron is proposed. This type of neuron is found in the inferotemporal cortex of monkeys. It responds strongly to groups ...
Peter Kruizinga, Nikolai Petkov