We consider the problem of estimating occurrence rates of rare events for extremely sparse data, using pre-existing hierarchies to perform inference at multiple resolutions. In pa...
Deepak Agarwal, Andrei Z. Broder, Deepayan Chakrab...
The kernel function plays a central role in kernel methods. In this paper, we consider the automated learning of the kernel matrix over a convex combination of pre-specified kerne...
The collaborative filtering approach to recommender systems predicts user preferences for products or services by learning past useritem relationships. In this work, we propose no...
The blogosphere has unique structural and temporal properties since blogs are typically used as communication media among human individuals. In this paper, we propose a novel tech...
Kernel machines have been shown as the state-of-the-art learning techniques for classification. In this paper, we propose a novel general framework of learning the Unified Kernel ...