Grammatical inference (or grammar inference) has been applied to various problems in areas such as computational biology, and speech and pattern recognition but its application to...
Techniques for plan recognition under uncertainty require a stochastic model of the plangeneration process. We introduce probabilistic state-dependent grammars (PSDGs) to represen...
We introduce a set of transformations on the set of all probability distributions over a finite state space, and show that these transformations are the only ones that preserve c...
We develop latent Dirichlet allocation with WORDNET (LDAWN), an unsupervised probabilistic topic model that includes word sense as a hidden variable. We develop a probabilistic po...
— This work is concerned with the problem of characterizing and computing probabilistic bisimulations of diffusion processes. A probabilistic bisimulation relation between two su...