This paper describes a class ofprobabilistic approximation algorithms based on bucket elimination which o er adjustable levels of accuracy ande ciency. We analyzethe approximation...
Loopy and generalized belief propagation are popular algorithms for approximate inference in Markov random fields and Bayesian networks. Fixed points of these algorithms correspo...
In this paper, we review parallel search techniques for approximating the global optimal solution of combinatorial optimization problems. Recent developments on parallel implementa...
Panos M. Pardalos, Leonidas S. Pitsoulis, Thelma D...
The problem of routing of sensor observations for optimal detection of a Markov random field (MRF) at a designated fusion center is analyzed. Assuming that the correlation structur...
We consider the facility location problem where each facility can serve at most U clients. We analyze a local search algorithm for this problem which uses only the operations of ad...
Ankit Aggarwal, L. Anand, Manisha Bansal, Naveen G...