In this work, the authors have evaluated almost 20 millions ensembles of classifiers generated by several methods. Trying to optimize those ensembles based on the nearest neighbou...
Guillaume Tremblay, Robert Sabourin, Patrick Maupi...
—Machine learning is inherently a multiobjective task. Traditionally, however, either only one of the objectives is adopted as the cost function or multiple objectives are aggreg...
In this paper we introduce model-based search as a unifying framework accommodating some recently proposed metaheuristics for combinatorial optimization such as ant colony optimiza...
Mark Zlochin, Mauro Birattari, Nicolas Meuleau, Ma...
In continuous black-box optimization, various stochastic local search techniques are often employed, with various remedies for fighting the premature convergence. This paper surve...
Several population-based methods (with origins in the world of evolutionary strategies and estimation-of-distribution algorithms) for black-box optimization in continuous domains ...