We introduce a new dimension to the widely studied on-line approximate string matching problem, by introducing an error threshold parameter so that the algorithm is allowed to mis...
We provide a new analysis of an efficient margin-based algorithm for selective sampling in classification problems. Using the so-called Tsybakov low noise condition to parametrize...
This paper describes and analyzes sporadic model building, which can be used to enhance the efficiency of the hierarchical Bayesian optimization algorithm (hBOA) and other advance...
We analyse a continued fraction algorithm (abbreviated CFA) for arbitrary dimension n showing that it produces simultaneous diophantine approximations which are up to the factor 2(...
This paper presents a gregarious particle swarm optimization algorithm (G-PSO) in which the particles explore the search space by aggressively scouting the local minima with the h...