Many emerging applications require documents to be repeatedly updated. Such documents include newsfeeds, webpages, and shared community resources such as Wikipedia. In this paper ...
Most learning to rank research has assumed that the utility of different documents is independent, which results in learned ranking functions that return redundant results. The fe...
Aleksandrs Slivkins, Filip Radlinski, Sreenivas Go...
We generalize the Winnow algorithm for learning disjunctions to learning subspaces of low rank. Subspaces are represented by symmetric projection matrices. The online algorithm ma...
In many practical applications, one is interested in generating a ranked list of items using information mined from continuous streams of data. For example, in the context of comp...
In order to minimize redundancy and optimize coverage of multiple user interests, search engines and recommender systems aim to diversify their set of results. To date, these dive...