Star networks were proposedrecently as an attractive alternative to the well-known hypercube models for interconnection networks. Extensive research has been performed that shows ...
Abstract. In this paper we solve the problem of computing exact continuous optimal curves and surfaces for image segmentation and 3D reconstruction, using a maximal flow approach ...
Learning Bayesian networks from data is an N-P hard problem with important practical applications. Several researchers have designed algorithms to overcome the computational comple...
We extend the well-known BFGS quasi-Newton method and its memory-limited variant LBFGS to the optimization of nonsmooth convex objectives. This is done in a rigorous fashion by ge...
Abstract— This paper explores the idea of neutrality in heuristic optimization algorithms. In particular, the effect of having multiple levels of neutrality in representations is...