Matroid theory gives us powerful techniques for understanding combinatorial optimization problems and for designing polynomial-time algorithms. However, several natural matroid pr...
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...
Decentralized sensor networks are collections of individual local sensors that observe a common phenomenon, quantize their observations, and send this quantized information to a ce...
Distributed problem solving by a multiagent system represents a promising approach to solving complex computational problems. However, many multiagent systems require certain degr...
—The noise-robust matching of two graphs is a hard combinatorial problem with practical importance in several domains. In practical applications, a unique solution for a given in...