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» Genetic Algorithms for Component Analysis
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138
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ICMCS
2005
IEEE
138views Multimedia» more  ICMCS 2005»
15 years 9 months ago
Overcomplete ICA-based Manmade Scene Classification
Principal Component Analysis (PCA) has been widely used to extract features for pattern recognition problems such as object recognition. Oliva and Torralba used “spatial envelop...
Matthew Boutell, Jiebo Luo
129
Voted
IPPS
2005
IEEE
15 years 9 months ago
MaTCH : Mapping Data-Parallel Tasks on a Heterogeneous Computing Platform Using the Cross-Entropy Heuristic
We propose in this paper a heuristic for mapping a set of interacting tasks of a parallel application onto a heterogeneous computing platform such as a computational grid. Our nov...
Soumya Sanyal, Sajal K. Das
133
Voted
ESWA
2006
154views more  ESWA 2006»
15 years 3 months ago
Artificial neural networks with evolutionary instance selection for financial forecasting
In this paper, I propose a genetic algorithm (GA) approach to instance selection in artificial neural networks (ANNs) for financial data mining. ANN has preeminent learning abilit...
Kyoung-jae Kim
131
Voted
SAC
2008
ACM
15 years 3 months ago
Computational methods for complex stochastic systems: a review of some alternatives to MCMC
We consider analysis of complex stochastic models based upon partial information. MCMC and reversible jump MCMC are often the methods of choice for such problems, but in some situ...
Paul Fearnhead
CEC
2007
IEEE
15 years 10 months ago
An evolutionary progressive multiple sequence alignment
Abstract This paper presents a new evolutionary method, namely, a Two Phase evolutionary algorithm for multiple sequence alignments. This method is composed of different types of e...
Farhana Naznin, Morikazu Nakamura, Takeo Okazaki, ...