Stochastic context-free grammars (SCFGs) have long been recognized as useful for a large variety of tasks including natural language processing, morphological parsing, speech reco...
In this paper, we, as well as Eskin, Lee, Stolfo [7] propose a method of prediction model. In their method, the program was characterized with both the order and the kind of system...
The paper describes an extensive experiment in inside-outside estimation of a lexicalized probabilistic context free grammar for German verbnal clauses. Grammar and formalism feat...
Franz Beil, Glenn Carroll, Detlef Prescher, Stefan...
In this paper we show how quantitative program logic [14] provides a formal framework in which to promote standard techniques of program analysis to a context where probability and...
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...