One of the major strengths of probabilistic topic modeling is the ability to reveal hidden relations via the analysis of co-occurrence patterns on dyadic observations, such as docu...
We introduce a robust probabilistic approach to modeling shape contours based on a lowdimensional, nonlinear latent variable model. In contrast to existing techniques that use obj...
Research in modeling and querying spatial data has primarily focused on traditional "crisp" spatial objects with exact location and spatial extent. More recent work, how...
Recent research has shown that collective classification in relational data often exhibit significant performance gains over conventional approaches that classify instances indi...
This paper presents a novel way of improving POS tagging on heterogeneous data. First, two separate models are trained (generalized and domain-specific) from the same data set by...