We present a nonparametric Bayesian model for multi-task learning, with a focus on feature selection in binary classification. The model jointly identifies groups of similar tas...
This paper studies document ranking under uncertainty. It is tackled in a general situation where the relevance predictions of individual documents have uncertainty, and are depen...
—For a large and evolving software system, the project team could receive a large number of bug reports. Locating the source code files that need to be changed in order to fix th...
Ranking methods like PageRank assess the importance of Web pages based on the current state of the rapidly evolving Web graph. The dynamics of the resulting importance scores, how...
Klaus Berberich, Srikanta J. Bedathur, Michalis Va...
Exploratory ad-hoc queries could return too many answers ? a phenomenon commonly referred to as "information overload". In this paper, we propose to automatically catego...