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 ...
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, ...
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...
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, ...
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...