We show how to build hierarchical, reduced-rank representation for large stochastic matrices and use this representation to design an efficient algorithm for computing the largest...
In order to minimize redundancy and optimize coverage of multiple user interests, search engines and recommender systems aim to diversify their set of results. To date, these dive...
In this paper we show the power of sampling techniques in designing efficient distributed algorithms. In particular, we show that using sampling techniques, on some networks, sele...
Active and passive measurements for topology discovery have known an impressive growth during the last decade. If a lot of work has been done regarding inter-domain topology discov...
We introduce a distributed algorithm for solving large scale Support Vector Machines (SVM) problems. The algorithm divides the training set into a number of processing nodes each ...