The 2- 1 sparse signal minimization problem can be solved efficiently by gradient projection. In many applications, the signal to be estimated is known to lie in some range of va...
James Hernandez, Zachary T. Harmany, Daniel Thomps...
The 2- 1 compressed sensing minimization problem can be solved efficiently by gradient projection. In imaging applications, the signal of interest corresponds to nonnegative pixel...
Zachary T. Harmany, Daniel Thompson, Rebecca Wille...
— We adopt the network coding approach to achieve minimum-cost multicast in interference-limited wireless networks where link capacities are functions of the signal-to-noise-plus...
—In this paper, we derive a time-complexity bound for the gradient projection method for optimal routing in data networks. This result shows that the gradient projection algorith...
We investigate the problem of estimating the proportion vector which maximizes the likelihood of a given sample for a mixture of given densities. We adapt a framework developed for...
David P. Helmbold, Yoram Singer, Robert E. Schapir...
We consider a parallel decomposition technique for solving the large quadratic programs arising in training the learning methodology Support Vector Machine. At each iteration of th...
As mobile ad hoc networks provide a wide range of possibly critical services, providing quality of service guarantees becomes an essential element. Yet there is a limited understa...