The problem of computing a maximum a posteriori (MAP) configuration is a central computational challenge associated with Markov random fields. There has been some focus on “tr...
Pradeep Ravikumar, Alekh Agarwal, Martin J. Wainwr...
The simplicity and low-overhead of random walks have made them a popular querying mechanism for Wireless Sensor Networks. However, most of the related work is of theoretical nature...
A semi-supervised multitask learning (MTL) framework is presented, in which M parameterized semi-supervised classifiers, each associated with one of M partially labeled data mani...
Graph-theory-based approaches have been used with great success when analyzing abstract properties of natural and artificial networks. However, these approaches have not factored...
Abstract—Existing work on cross-layer optimization for wireless networks adopts simple physical-layer models, i.e., treating interference as noise. In this paper, we adopt a dete...