We show that randomization can lead to significant improvements for a few fundamental problems in distributed tracking. Our basis is the count-tracking problem, where there are k...
Estimation of Distribution Algorithms (EDAs) are a class of evolutionary algorithms that use machine learning techniques to solve optimization problems. Machine learning is used t...
Consider a network vulnerable to viral infection. The system security software can guarantee safety only to a limited part of the network. Such limitations result from economy cos...
Marios Mavronicolas, Vicky G. Papadopoulou, Anna P...
—In this paper we study the distributed multi-channel power allocation for spectrum sharing cognitive radio networks with QoS guarantee. We formulate this problem as a noncoopera...
In this paper, we present a novel entropy estimator for a given set of samples drawn from an unknown probability density function (PDF). Counter to other entropy estimators, the e...