This paper presents two Markov chain Monte Carlo (MCMC) algorithms for Bayesian inference of probabilistic context free grammars (PCFGs) from terminal strings, providing an altern...
Mark Johnson, Thomas L. Griffiths, Sharon Goldwate...
We present a simple, easily implemented spectral learning algorithm which applies equally whether we have no supervisory information, pairwise link constraints, or labeled example...
Sepandar D. Kamvar, Dan Klein, Christopher D. Mann...
It has been shown that a class of probabilistic domain models cannot be learned correctly by several existing algorithms which employ a single-link lookahead search. When a multil...
This paper presents a probabilistic grammar approach to the recognition of complex events in videos. Firstly, based on the original motion features, a rule induction algorithm is a...
Language modeling is an effective and theoretically attractive probabilistic framework for text information retrieval. The basic idea of this approach is to estimate a language mo...