Planning under uncertainty is an important and challenging problem in multiagent systems. Multiagent Partially Observable Markov Decision Processes (MPOMDPs) provide a powerful fr...
We address the problem of classification in partially labeled networks (a.k.a. within-network classification) where observed class labels are sparse. Techniques for statistical re...
Brian Gallagher, Hanghang Tong, Tina Eliassi-Rad, ...
—We consider opportunistic communications over multiple channels where the state (“good” or “bad”) of each channel evolves as independent and identically distributed Mark...
In the presence of multiple delay faults, automated diagnostic procedures that make a single fault assumption may give an incorrect diagnosis. In this paper, a systematic approach...
Background: Receiver operating characteristic (ROC) curves are useful tools to evaluate classifiers in biomedical and bioinformatics applications. However, conclusions are often r...