The interaction among variables of an optimization problem is known as epistasis, and its degree is an important measure for the nonlinearity of the problem. We address the proble...
We consider an optimization problem in probabilistic inference: Given n hypotheses Hj, m possible observations Ok, their conditional probabilities pk j, and a particular Ok, selec...
A genetic local search (GLS) algorithm, which is a combination technique of genetic algorithm and local search, for the unconstrained binary quadratic programming problem (BQP) is...
In this paper, we describe a new incomplete approach for solving constraint satisfaction problems (CSPs) based on the ant colony optimization (ACO) metaheuristic. The idea is to us...
Abstract. Bayesian inference provides a powerful framework to optimally integrate statistically learned prior knowledge into numerous computer vision algorithms. While the Bayesian...