— This paper studies consensus seeking over noisy networks with time-varying noise statistics. Stochastic approximation type algorithms can ensure consensus in mean square and wi...
The complexity, approximation and algorithmic issues of several clustering problems are studied. These non-traditional clustering problems arise from recent studies in microarray ...
Optimization problems with a nuclear norm regularization, such as e.g. low norm matrix factorizations, have seen many applications recently. We propose a new approximation algorit...
Significant advances have been made in the last two decades for the effective solution of mixed integer non-linear programming (MINLP) problems, mainly by exploiting the special s...
Abstract. This paper proposes an approximate methodology for solving Markov models that compete for limited resources and retry when access fails, like those arising in mobile cell...