Abstract--Multiple instance learning (MIL) is a recently researched technique used for learning a target concept in the presence of noise. Previously, a random set framework for mu...
In this paper we consider the problem of computing the expected hitting time to a vertex for random walks on graphs. We give a method for computing an upper bound on the expected ...
We show that random graphs in the preferential connectivity model have constant conductance, and hence have worst-case routing congestion that scales logarithmically with the numb...
Milena Mihail, Christos H. Papadimitriou, Amin Sab...
We consider the classical rumor spreading problem, where a piece of information must be disseminated from a single node to all n nodes of a given network. We devise two simple pus...
George Giakkoupis, Thomas Sauerwald, He Sun, Phili...
Tensors naturally model many real world processes which generate multi-aspect data. Such processes appear in many different research disciplines, e.g, chemometrics, computer visio...