The ability to model cognitive agents depends crucially on being able to encode and infer with contextual information at many levels (such as situational, psychological, social, or...
Srini Narayanan, Katie Sievers, Steven J. Maiorano
: This paper proposes a new inference approach for Chinese probabilistic context-free grammar, which implements the EM algorithm based on the bracket matching schemes. By utilizing...
We present a novel probabilistic multiple cause model for binary observations. In contrast to other approaches, the model is linear and it infers reasons behind both observed and ...
We use a generative history-based model to predict the most likely derivation of a dependency parse. Our probabilistic model is based on Incremental Sigmoid Belief Networks, a rec...
Probabilistic database systems have successfully established themselves as a tool for managing uncertain data. However, much of the research in this area has focused on efficient...