We introduce a new method for data clustering based on a particular Gaussian mixture model (GMM). Each cluster of data, modeled as a GMM into an input space, is interpreted as a hy...
Many areas in power systems require solving one or more nonlinear optimization problems. While analytical methods might suffer from slow convergence and the curse of dimensionality...
Y. del Valle, Ganesh K. Venayagamoorthy, Salman Mo...
In this paper, we review a recently developed class of algorithms that solve global problems in unit distance wireless networks by means of local algorithms. A local algorithm is ...
Abstract. Dechter et al. [5] proposed solving the Temporal Constraint Satisfaction Problem (TCSP) by modeling it as a metaCSP, which is a finite CSP with a unique global constraint...
In this paper, we examine some computational issues on finite element discretization of the p-Laplacian. We introduced a class of descent methods with multi-grid finite element ...