A given entity, representing a person, a location or an organization, may be mentioned in text in multiple, ambiguous ways. Understanding natural language requires identifying whe...
Probabilistic topic models have become popular as methods for dimensionality reduction in collections of text documents or images. These models are usually treated as generative m...
Online forum discussions are emerging as valuable information repository, where knowledge is accumulated by the interaction among users, leading to multiple threads with structure...
Hongning Wang, Chi Wang, ChengXiang Zhai, Jiawei H...
We propose a class of graphical models appropriate for structure prediction problems where the model structure is a function of the output structure. Incremental Sigmoid Belief Ne...
This paper studies issues relating to the parameterization of probability distributions over binary data sets. Several such parameterizations of models for binary data are known, ...
David Buchman, Mark W. Schmidt, Shakir Mohamed, Da...