We develop a variant of the Nelder-Mead (NM) simplex search procedure for stochastic simulation optimization that is designed to avoid many of the weaknesses encumbering such dire...
A discretized version of a continuous optimization problem is considered for the case where data is obtained from a set of dispersed sensor nodes and the overall metric is a sum o...
—Multiobjective optimization problems have been widely addressed using evolutionary computation techniques. However, when dealing with more than three conflicting objectives (th...
Mario Garza-Fabre, Gregorio Toscano Pulido, Carlos...
Abstract. We present a technique for learning the parameters of a continuousstate Markov random field (MRF) model of optical flow, by minimizing the training loss for a set of grou...
We propose a method for fine grain QoS control of real-time applications. The method allows adapting the overall system behavior by adequately setting the quality level parameter...
Jacques Combaz, Jean-Claude Fernandez, Thierry Lep...