We provide a novel formulation for computing median filter with spatial regularization as minimizing a cost function composed of absolute value norms. We turn this cost minimizat...
—We study two convex optimization problems in a multi-class M/G/1 queue with adjustable service rates: minimizing convex functions of the average delay vector, and minimizing ave...
We present a theoretical analysis of supervised ranking, providing necessary and sufficient conditions for the asymptotic consistency of algorithms based on minimizing a surrogate...
Many applications in multiagent learning are essentially convex optimization problems in which agents have only limited communication and partial information about the function be...
Renato L. G. Cavalcante, Alex Rogers, Nicholas R. ...
Abstract. In this paper, we consider the minimization of a relevant energy consumption related cost function in the context of sensor networks where correlated sources are generate...