A key problem in reinforcement learning is finding a good balance between the need to explore the environment and the need to gain rewards by exploiting existing knowledge. Much ...
We introduce Bayesian Coalitional Games1 (BCGs), a generalization of classical coalitional games to settings with uncertainties. We define the semantics of BCG using the partition...
Compiling Bayesian networks (BNs) is one of the hot topics in the area of probabilistic modeling and processing. In this paper, we propose a new method of compiling BNs into multi...
Documents often have inherently parallel structure: they may consist of a text and ries, or an abstract and a body, or parts presenting alternative views on the same problem. Reve...
This paper demonstrates a new method for leveraging unstructured annotations to infer semantic document properties. We consider the domain of product reviews, which are often anno...
S. R. K. Branavan, Harr Chen, Jacob Eisenstein, Re...