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CP
2004
Springer
14 years 1 months ago
Heuristic Selection for Stochastic Search Optimization: Modeling Solution Quality by Extreme Value Theory
The success of stochastic algorithms is often due to their ability to effectively amplify the performance of search heuristics. This is certainly the case with stochastic sampling ...
Vincent A. Cicirello, Stephen F. Smith
RECOMB
2002
Springer
14 years 8 months ago
Simulating a Coalescent Process with Recombination and Ascertainment
A new method is presented for use in simulating samples of disease and normal chromosomes bearing multiple linked genetic markers under a neutral model of mutation, genetic drift, ...
Ying Wang, Bruce Rannala
ECAI
2010
Springer
13 years 8 months ago
EP for Efficient Stochastic Control with Obstacles
Abstract. We address the problem of continuous stochastic optimal control in the presence of hard obstacles. Due to the non-smooth character of the obstacles, the traditional appro...
Thomas Mensink, Jakob J. Verbeek, Bert Kappen
GECCO
2005
Springer
132views Optimization» more  GECCO 2005»
14 years 1 months ago
A statistical learning theory approach of bloat
Code bloat, the excessive increase of code size, is an important issue in Genetic Programming (GP). This paper proposes a theoretical analysis of code bloat in the framework of sy...
Sylvain Gelly, Olivier Teytaud, Nicolas Bredeche, ...
PPOPP
2005
ACM
14 years 1 months ago
A sampling-based framework for parallel data mining
The goal of data mining algorithm is to discover useful information embedded in large databases. Frequent itemset mining and sequential pattern mining are two important data minin...
Shengnan Cong, Jiawei Han, Jay Hoeflinger, David A...