We propose to solve the combinatorial problem of finding the highest scoring Bayesian network structure from data. This structure learning problem can be viewed as an inference pr...
Tommi Jaakkola, David Sontag, Amir Globerson, Mari...
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 ...
We propose a class of Bayesian networks appropriate for structured prediction problems where the Bayesian network's model structure is a function of the predicted output stru...
The increasing availability of electronic communication data, such as that arising from e-mail exchange, presents social and information scientists with new possibilities for char...
R. Dean Malmgren, Jake M. Hofman, Luis A. N. Amara...
Occlusion is a difficult problem for appearance-based target tracking, especially when we need to track multiple targets simultaneously and maintain the target identities during t...