Robust, real-time tracking of objects from visual data requires probabilistic fusion of multiple visual cues. Previous approaches have either been ad hoc or relied on a Bayesian n...
We study graphical modeling in the case of stringvalued random variables. Whereas a weighted finite-state transducer can model the probabilistic relationship between two strings, ...
Abstract. The stochastic satisfiability modulo theories (SSMT) problem is a generalization of the SMT problem on existential and randomized (aka. stochastic) quantification over di...
We present the first PAC bounds for learning parameters of Conditional Random Fields [12] with general structures over discrete and real-valued variables. Our bounds apply to com...
We propose Markov random fields (MRFs) as a probabilistic mathematical model for unifying approaches to multi-robot coordination or, more specifically, distributed action selectio...
Jesse Butterfield, Odest Chadwicke Jenkins, Brian ...