Probabilistic modeling has been a dominant approach in Machine Learning research. As the field evolves, the problems of interest become increasingly challenging and complex. Makin...
Ming-Wei Chang, Lev-Arie Ratinov, Nicholas Rizzolo...
Recent research has shown the benefit of framing problems of imitation learning as solutions to Markov Decision Problems. This approach reduces learning to the problem of recoveri...
Brian Ziebart, Andrew L. Maas, J. Andrew Bagnell, ...
We present text replays, a method for generating labels that can be used to train classifiers of student behavior. We use this method to label data as to whether students are gamin...
Ryan Shaun Joazeiro de Baker, Adriana M. J. B. de ...
Accurate entity resolution is sometimes impossible simply due to insufficient information. For example, in research paper author name resolution, even clever use of venue, title ...
Compiling Bayesian networks has proven an effective approach for inference that can utilize both global and local network structure. In this paper, we define a new method of comp...