Abstract--This paper develops an optimal decentralized algorithm for sparse signal recovery and demonstrates its application in monitoring localized phenomena using energy-constrai...
— In this paper, we present a distributed algorithm for detecting redundancies in a sensor network with no location information. We demonstrate how, in the absence of localizatio...
We study the problem of aggregating data from a sparse set of nodes in a wireless sensor network. This is a common situation when a sensor network is deployed to detect relatively...
Jie Gao, Leonidas J. Guibas, Nikola Milosavljevic,...
Background: There is an increasing demand to assemble and align large-scale biological sequence data sets. The commonly used multiple sequence alignment programs are still limited...
Large scale learning is often realistic only in a semi-supervised setting where a small set of labeled examples is available together with a large collection of unlabeled data. In...