Probabilistic inference techniques can be used to estimate variable bias, or the proportion of solutions to a given SAT problem that fix a variable positively or negatively. Metho...
This work addresses the problem of processing continuous nearest neighbor (NN ) queries for moving objects trajectories when the exact position of a given object at a particular t...
Probabilistic reasoning with multiply sectioned Bayesian networks (MSBNs) has been successfully applied in static domains under the cooperative multiagent paradigm. Probabilistic ...
We propose and analyze a distribution learning algorithm for variable memory length Markov processes. These processes can be described by a subclass of probabilistic nite automata...
We present a novel approach, based on probabilistic formal methods, to developing cross-layer resource optimization policies for resource limited distributed systems. One objective...
Minyoung Kim, Mark-Oliver Stehr, Carolyn L. Talcot...