Empirical divergence maximization is an estimation method similar to empirical risk minimization whereby the Kullback-Leibler divergence is maximized over a class of functions tha...
Abstract. We study positive measures that are solutions to an abstract optimisation problem, which is a generalisation of a classical variational problem with a constraint on infor...
—In this paper we develop a distributed rate control algorithm for multiple-unicast-sessions when network coding is allowed. Building on our recent flow-based characterization o...
Abdallah Khreishah, Chih-Chun Wang, Ness B. Shroff
One of the key factors for the success of recent energy
minimization methods is that they seek to compute global
solutions. Even for non-convex energy functionals, optimization
...
Petter Strandmark, Fredrik Kahl, Niels Chr. Overga...
Geometric reconstruction problems in computer vision are often solved by minimizing a cost function that combines the reprojection errors in the 2D images. In this paper, we show t...