We propose a probabilistic interpretation of Propositional Dynamic Logic (PDL). We show that logical and behavioral equivalence are equivalent over general measurable spaces. This...
Abstract. We develop a Bayesian approach to concept learning for crowdsourcing applications. A probabilistic belief over possible concept definitions is maintained and updated acc...
Paolo Viappiani, Sandra Zilles, Howard J. Hamilton...
—Identifying unusual or unique characteristics of an observed sample in useful in forensics in general and handwriting analysis in particular. Rarity is formulated as the probabi...
Many semantic parsing models use tree transformations to map between natural language and meaning representation. However, while tree transformations are central to several state-...
Learning visual models of object categories notoriously requires thousands of training examples; this is due to the diversity and richness of object appearance which requires mode...