The growth of Internet commerce has stimulated the use of collaborative filtering (CF) algorithms as recommender systems. Such systems leverage knowledge about the known preferenc...
David M. Pennock, Eric Horvitz, Steve Lawrence, C....
Dynamic Bayesian networks (DBNs) offer an elegant way to integrate various aspects of language in one model. Many existing algorithms developed for learning and inference in DBNs ...
Neural probabilistic language models (NPLMs) have been shown to be competitive with and occasionally superior to the widely-used n-gram language models. The main drawback of NPLMs...
Nonparametric Bayesian models are often based on the assumption that the objects being modeled are exchangeable. While appropriate in some applications (e.g., bag-ofwords models f...
Kurt T. Miller, Thomas L. Griffiths, Michael I. Jo...
We describe a class of translation model in which a set of input variants encoded as a context-free forest is translated using a finitestate translation model. The forest structur...