Abstract- Sequential parameter optimization is a heuristic that combines classical and modern statistical techniques to improve the performance of search algorithms. To demonstrate...
Thomas Bartz-Beielstein, Christian Lasarczyk, Mike...
Differential evolution (DE) is well known as a simple and efficient scheme for global optimization over continuous spaces. In this paper we present two new, improved variants of D...
Background: In proteomic analysis, MS/MS spectra acquired by mass spectrometer are assigned to peptides by database searching algorithms such as SEQUEST. The assignations of pepti...
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 ...
Background: Similarity inference, one of the main bioinformatics tasks, has to face an exponential growth of the biological data. A classical approach used to cope with this data ...