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» Machine learning problems from optimization perspective
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ICDM
2005
IEEE
153views Data Mining» more  ICDM 2005»
16 years 8 days ago
Speculative Markov Blanket Discovery for Optimal Feature Selection
In this paper we address the problem of learning the Markov blanket of a quantity from data in an efficient manner. Markov blanket discovery can be used in the feature selection ...
Sandeep Yaramakala, Dimitris Margaritis
BMCBI
2006
158views more  BMCBI 2006»
15 years 6 months ago
Parallelization of multicategory support vector machines (PMC-SVM) for classifying microarray data
Background: Multicategory Support Vector Machines (MC-SVM) are powerful classification systems with excellent performance in a variety of data classification problems. Since the p...
Chaoyang Zhang, Peng Li, Arun Rajendran, Youping D...
ICML
2006
IEEE
16 years 7 months ago
Learning a kernel function for classification with small training samples
When given a small sample, we show that classification with SVM can be considerably enhanced by using a kernel function learned from the training data prior to discrimination. Thi...
Tomer Hertz, Aharon Bar-Hillel, Daphna Weinshall
GECCO
2011
Springer
236views Optimization» more  GECCO 2011»
14 years 10 months ago
Online, GA based mixture of experts: a probabilistic model of ucs
In recent years there have been efforts to develop a probabilistic framework to explain the workings of a Learning Classifier System. This direction of research has met with lim...
Narayanan Unny Edakunni, Gavin Brown, Tim Kovacs
176
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GECCO
2009
Springer
150views Optimization» more  GECCO 2009»
16 years 1 months ago
Discrete dynamical genetic programming in XCS
A number of representation schemes have been presented for use within Learning Classifier Systems, ranging from binary encodings to neural networks. This paper presents results fr...
Richard Preen, Larry Bull