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101
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GECCO
2008
Springer
238views Optimization» more  GECCO 2008»
15 years 1 months ago
Using multiple offspring sampling to guide genetic algorithms to solve permutation problems
The correct choice of an evolutionary algorithm, a genetic representation for the problem being solved (as well as their associated variation operators) and the appropriate values...
Antonio LaTorre, José Manuel Peña, V...
134
Voted
EUROGP
2010
Springer
217views Optimization» more  EUROGP 2010»
15 years 7 months ago
Evolving Genes to Balance a Pole
We discuss how to use a Genetic Regulatory Network as an evolutionary representation to solve a typical GP reinforcement problem, the pole balancing. The network is a modified ver...
Miguel Nicolau, Marc Schoenauer, Wolfgang Banzhaf
97
Voted
GECCO
2008
Springer
130views Optimization» more  GECCO 2008»
15 years 1 months ago
Parsimony pressure made easy
The parsimony pressure method is perhaps the simplest and most frequently used method to control bloat in genetic programming. In this paper we first reconsider the size evolutio...
Riccardo Poli, Nicholas Freitag McPhee
95
Voted
VTC
2010
IEEE
172views Communications» more  VTC 2010»
14 years 11 months ago
Turbo Source Compression with Jointly Optimized Inner Irregular and Outer Irregular Codes
—In this paper, we present a near-lossless compression scheme for scalar-quantized source codec parameters based on iterative source-channel decoding (ISCD). The scheme is compar...
Laurent Schmalen, Peter Vary, Thorsten Clevorn, Ma...
113
Voted
CISS
2008
IEEE
15 years 7 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