We study metric learning as a problem of information retrieval. We present a general metric learning algorithm, based on the structural SVM framework, to learn a metric such that ...
Abstract. A useful ability for search engines is to be able to rank objects with novelty and diversity: the top k documents retrieved should cover possible interpretations of a que...
Abstract. In this paper we address the problem of building a compressed self-index that, given a distribution for the pattern queries and a bound on the space occupancy, minimizes ...
Traditional approaches to rule-based information extraction (IE) have primarily been based on regular expression grammars. However, these grammar-based systems have difficulty scal...
Frederick Reiss, Sriram Raghavan, Rajasekar Krishn...
Maintaining materialized views that have join conditions between arbitrary pairs of data sources possibly with cycles is critical for many applications. In this work, we model vie...