This paper investigates the problem of automatically learning how to restructure the reward function of a Markov decision process so as to speed up reinforcement learning. We begi...
The problems of dimension reduction and inference of statistical dependence are addressed by the modeling framework of learning gradients. The models we propose hold for Euclidean...
Query segmentation is the process of taking a user’s search-engine query and dividing the tokens into individual phrases or semantic units. Identification of these query segmen...
An unsupervised probabilistic learning framework for normalizing product records across different retailer Web sites is presented. Our framework decomposes the problem into two ta...
Digitization of information, the rise of the World Wide Web, and the development of new means for information creation, production and dissemination place new strains on the legal...