This paper proposes a novel hierarchical learning strategy to deal with the data sparseness problem in relation extraction by modeling the commonality among related classes. For e...
2004 brought a landmark event in the changes to regulations governing hours of service for truck drivers. This paper describes an effort utilizing modeling and simulation for eval...
A serious problem in learning probabilistic models is the presence of hidden variables. These variables are not observed, yet interact with several of the observed variables. As s...
Gal Elidan, Noam Lotner, Nir Friedman, Daphne Koll...
learning (EBL) component. In this paper we provide a brief review of FOIL and FOCL, then discuss how operationalizing a domain theory can adversely affect the accuracy of a learned...
Users of search engines express their needs as queries, typically consisting of a small number of terms. The resulting search engine query logs are valuable resources that can be ...
Milad Shokouhi, Justin Zobel, Seyed M. M. Tahaghog...