Sparse methods for supervised learning aim at finding good linear predictors from as few variables as possible, i.e., with small cardinality of their supports. This combinatorial ...
In this paper, we discuss semidefinite relaxation techniques for computing minimal size ellipsoids that bound the solution set of a system of uncertain linear equations. The propo...
In this paper, we address the problem of real-time video streaming over wireless LANs for both unicast and multicast transmission. The wireless channel is modeled as a packet-erasu...
Abhik Majumdar, Daniel Grobe Sachs, Igor Kozintsev...
Abstract—The k-means method is a simple and fast clustering technique that exhibits the problem of specifying the optimal number of clusters preliminarily. We address the problem...
"Constraint satisfaction is a general problem in which the goal is to find values for a set of variables that will satisfy a given set of constraints. It is the core of many a...