— Ergodic stochastic optimization (ESO) algorithms are proposed to solve resource allocation problems that involve a random state and where optimality criteria are expressed in t...
This paper describes a method for improving the final accuracy and the convergence speed of Particle Swarm Optimization (PSO) by adapting its inertia factor in the velocity updati...
Consider a fully connected network where up to t processes may crash, and all processes start in an arbitrary memory state. The self-stabilizing firing squad problem consists of e...
Efficient design of wireless networks requires implementation of cross-layer algorithms that exploit channel state information. Capitalizing on convex optimization and stochastic...
Markov Random Fields (MRFs) are ubiquitous in lowlevel computer vision. In this paper, we propose a new approach to the optimization of multi-labeled MRFs. Similarly to -expansion...