In this paper we compare the average performance of one class of low-discrepancy quasi-Monte Carlo sequences for global optimization. Weiner measure is assumed as the probability ...
In this paper we compare the average performance of Monte Carlo methods for global optimization with non-adaptive deterministic alternatives. We analyze the behavior of the algori...
A Quasi-Monte-Carlo method based on the computation of a surrogate model of the fitness function is proposed, and its convergence at super-linear rate 3/2 is proved under rather ...
Abstract— We present a unifying framework for continuous optimization and sampling. This framework is based on Gaussian Adaptation (GaA), a search heuristic developed in the late...
Adaptive Monte Carlo methods are specialized Monte Carlo simulation techniques where the methods are adaptively tuned as the simulation progresses. The primary focus of such techn...