We present a graph-theoretic approach to discover storylines from search results. Storylines are windows that offer glimpses into interesting themes latent among the top search re...
This paper consists of two parts. The first part is the development of a datadriven Kalman filter for a non-uniformly sampled multirate (NUSM) system, including identification of ...
We present a framework for generating procedure summaries that are precise -- applying the summary in a given context yields the same result as re-analyzing the procedure in that ...
We consider the problem of obtaining the approximate maximum a posteriori estimate of a discrete random field characterized by pairwise potentials that form a truncated convex mod...
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 ...