Abstract— In this paper we present a dual-based decomposition method, called here the proximal center method, to solve distributed model predictive control (MPC) problems for cou...
In this paper, we cast discriminative training problems into standard linear programming (LP) optimization. Besides being convex and having globally optimal solution(s), LP progra...
This paper addresses the image representation problem in visual sensor networks. We propose a new image representation scheme based on compressive sensing (CS) because compressive...
In this paper, we present two linear-size external memory data structures for approximate range searching. Our first structure, the BAR-B-tree, stores a set of N points in Rd and ...
— A key step in many statistical learning methods used in machine learning involves solving a convex optimization problem containing one or more hyper-parameters that must be sel...
Kristin P. Bennett, Jing Hu, Xiaoyun Ji, Gautam Ku...