—We describe and evaluate a suite of distributed and computationally efficient algorithms for solving a class of convex optimization problems in wireless sensor networks. The pr...
Loopy and generalized belief propagation are popular algorithms for approximate inference in Markov random fields and Bayesian networks. Fixed points of these algorithms correspo...
The simulation of mobility models such as the random waypoint often cause subtle problems, for example the decay of average speed as the simulation progresses, a difference betwee...
We propose a convex-concave programming approach for the labeled weighted graph matching problem. The convex-concave programming formulation is obtained by rewriting the weighted ...
Mikhail Zaslavskiy, Francis Bach, Jean-Philippe Ve...
This work shows asymptotic convergence to global optima for a family of dynamically scaled genetic programming systems where the underlying population consists of a fixed number o...