Sparse graphical models have proven to be a flexible class of multivariate probability models for approximating high-dimensional distributions. In this paper, we propose techniques...
Vincent Y. F. Tan, Sujay Sanghavi, John W. Fisher ...
In this paper we consider the application of a homotopy-continuation based method for finding interference alignment (IA) solutions for the deterministic K-user multiple-input mu...
—It is well-known that the application of directional antennas can help conserve bandwidth and energy consumption in wireless networks. Thus, to achieve efficiency in wireless n...
Ling Ding, Weili Wu, James Willson, Hongjie Du, Wo...
—In this work we address the problem of state estimation in dynamical systems using recent developments in compressive sensing and sparse approximation. We formulate the traditio...
Adam Charles, Muhammad Salman Asif, Justin K. Romb...
Abstract. The Bayesian approach to machine learning amounts to inferring posterior distributions of random variables from a probabilistic model of how the variables are related (th...