The crucial issue in many classification applications is how to achieve the best possible classifier with a limited number of labeled data for training. Training data selection is ...
In this paper we develop a variant of a previously proposed method the regenerative randomization method for the transient analysis of dependability performability models. The va...
An O(log n) time, n processor randomized algorithm for computing the k-nearest neighbor graph of n points in d dimensions, for fixed d and k is presented. The method is based on t...
The parallelization of two applications in symmetric cryptography is considered: block ciphering and a new method based on random sampling for the selection of basic substitution ...
Vincent Danjean, Roland Gillard, Serge Guelton, Je...
Variable importance measures for random forests have been receiving increased attention as a means of variable selection in many classification tasks in bioinformatics and relate...