Energy efficiency is a critical issue in designing sensor networks, as the nodes have limited battery power. In this paper we propose to move the BS so as to prolong the network l...
This article studies disruption tolerant networks (DTNs) where each node knows the probabilistic distribution of contacts with other nodes. It proposes a framework that allows one ...
Selection of the topology of a neural network and correct parameters for the learning algorithm is a tedious task for designing an optimal artificial neural...
We propose a new class of game-theoretic models for network formation in which strategies are not directly related to edge choices, but instead correspond more generally to the ex...
Christian Borgs, Jennifer T. Chayes, Jian Ding, Br...
The paper presents a new sampling methodology for Bayesian networks that samples only a subset of variables and applies exact inference to the rest. Cutset sampling is a network s...