This paper introduces a simple and very general theory of compressive sensing. In this theory, the sensing mechanism simply selects sensing vectors independently at random from a ...
This paper presents several novel theoretical results regarding the recovery of a low-rank matrix from just a few measurements consisting of linear combinations of the matrix entr...
We consider the problem of estimating a deterministic sparse vector x0 from underdetermined measurements Ax0 +w, where w represents white Gaussian noise and A is a given determinis...
Variable selection is an important and practical problem that arises in analysis of many high-dimensional datasets. Convex optimization procedures that arise from relaxing the NP-...
We present a question answering (QA) system which learns how to detect and rank answer passages by analyzing questions and their answers (QA pairs) provided as training data. We b...