We present a phrasal synchronous grammar model of translational equivalence. Unlike previous approaches, we do not resort to heuristics or constraints from a word-alignment model,...
Phil Blunsom, Trevor Cohn, Chris Dyer, Miles Osbor...
We propose a novel method for inferring whether X causes Y or vice versa from joint observations of X and Y . The basic idea is to model the observed data using probabilistic late...
We propose a new model of human concept learning that provides a rational analysis for learning of feature-based concepts. This model is built upon Bayesian inference for a gramma...
Noah D. Goodman, Joshua B. Tenenbaum, Jacob Feldma...
This paper deals with the problem of inference under uncertain information. This is a generalization of a paper of Cardona et al. (1991a) where rules were not allowed to contain n...
Given a model family and a set of unlabeled examples, one could either label specific examples or state general constraints--both provide information about the desired model. In g...