We present a coreference resolver called BABAR that uses contextual role knowledge to evaluate possible antecedents for an anaphor. BABAR uses information extraction patterns to i...
Covering and packing integer programs model a large family of combinatorial optimization problems. The current-best approximation algorithms for these are an instance of the basic...
We generalise the Gaussian process (GP) framework for regression by learning a nonlinear transformation of the GP outputs. This allows for non-Gaussian processes and non-Gaussian ...
Edward Snelson, Carl Edward Rasmussen, Zoubin Ghah...
We investigate the use of probabilistic models and cost-benefit analyses to guide the operation of a Web-based question-answering system. We first provide an overview of research ...
David Azari, Eric Horvitz, Susan T. Dumais, Eric B...
Learning with hidden variables is a central challenge in probabilistic graphical models that has important implications for many real-life problems. The classical approach is usin...