Estimation of distribution algorithms (EDAs) are population-based heuristic search methods that use probabilistic models of good solutions to guide their search. When applied to co...
In this paper, we propose a new methodology to build latent variables that are optimal if a nonlinear model is used afterward. This method is based on Nonparametric Noise Estimatio...
—With continuous technology scaling, soft errors are becoming an increasingly important design concern even for earth-bound applications. While compiler approaches have the poten...
This paper describes a novel approach to nd a tighter bound of the transformation of the Min-Max problems into the one of Least-Square Estimation. It is well known that the above ...
Minimizing the rank of a matrix subject to constraints is a challenging problem that arises in many applications in machine learning, control theory, and discrete geometry. This c...