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GECCO
2005
Springer
158views Optimization» more  GECCO 2005»
13 years 10 months ago
A genetic algorithm approach to the selection of near-optimal subsets from large sets
The problem attempted in this paper is to select a sample from a large set where the sample is required to have a particular average property. The problem can be expressed as an o...
P. Whiting, P. W. Poon, J. N. Carter
GECCO
2004
Springer
144views Optimization» more  GECCO 2004»
13 years 10 months ago
Feature Subset Selection, Class Separability, and Genetic Algorithms
Abstract. The performance of classification algorithms in machine learning is affected by the features used to describe the labeled examples presented to the inducers. Therefore,...
Erick Cantú-Paz
JMLR
2012
11 years 7 months ago
SpeedBoost: Anytime Prediction with Uniform Near-Optimality
We present SpeedBoost, a natural extension of functional gradient descent, for learning anytime predictors, which automatically trade computation time for predictive accuracy by s...
Alexander Grubb, Drew Bagnell
IJIT
2004
13 years 6 months ago
Genetic Algorithm for Feature Subset Selection with Exploitation of Feature Correlations from Continuous Wavelet Transform: a re
A genetic algorithm (GA) based feature subset selection algorithm is proposed in which the correlation structure of the features is exploited. The subset of features is validated a...
Gert Van Dijck, Marc M. Van Hulle, M. Wevers
CISS
2008
IEEE
13 years 11 months ago
Near optimal lossy source coding and compression-based denoising via Markov chain Monte Carlo
— We propose an implementable new universal lossy source coding algorithm. The new algorithm utilizes two wellknown tools from statistical physics and computer science: Gibbs sam...
Shirin Jalali, Tsachy Weissman