When text categorization is applied to complex tasks, it is tedious and expensive to hand-label the large amounts of training data necessary for good performance. In this paper, we...
We study the computational and sample complexity of parameter and structure learning in graphical models. Our main result shows that the class of factor graphs with bounded degree...
In this paper, we consider a contaminated network with an intruder. The task for the mobile agents is to decontaminate all hosts while preventing a recontamination and to do so as ...
Surveillance systems that operate continuously generate large volumes of data. One such system is described here, continuously tracking and storing observations taken from multiple...
We explore a general Bayesian active learning setting, in which the learner can ask arbitrary yes/no questions. We derive upper and lower bounds on the expected number of queries r...