Abstract. We investigate the quality of solutions obtained from sample-average approximations to two-stage stochastic linear programs with recourse. We use a recently developed sof...
We give the first constant-factor approximation algorithm for Sparsest-Cut with general demands in bounded treewidth graphs. In contrast to previous algorithms, which rely on the f...
Eden Chlamtac, Robert Krauthgamer, Prasad Raghaven...
Abstract. We propose a unifying framework for polyhedral approximation in convex optimization. It subsumes classical methods, such as cutting plane and simplicial decomposition, bu...
An efficient method for rate control is illustrated for joint source-channel rate selection and for encoding under multiple leaky bucket buffer constraints. This method shows adva...
Quadratic program relaxations are proposed as an alternative to linear program relaxations and tree reweighted belief propagation for the metric labeling or MAP estimation problem...