Support vector machines are trained by solving constrained quadratic optimization problems. This is usually done with an iterative decomposition algorithm operating on a small wor...
The use of frequent itemsets has been limited by the high computational cost as well as the large number of resulting itemsets. In many real-world scenarios, however, it is often ...
The MAP (maximum a posteriori hypothesis) problem in Bayesian networks is to find the most likely states of a set of variables given partial evidence on the complement of that set...
In this paper we present a Differential Evolution based algorithm used to solve the Radio Network Design (RND) problem. This problem consists in determining the optimal locations ...
Abstract--In this paper, we investigate the use of messagepassing algorithms for the problem of finding the max-weight independent set (MWIS) in a graph. First, we study the perfor...