Given a matrix M of low-rank, we consider the problem of reconstructing it from noisy observations of a small, random subset of its entries. The problem arises in a variety of app...
Raghunandan H. Keshavan, Andrea Montanari, Sewoong...
Abstract. This paper presents an algorithm for the estimation of multiple regions with unknown shapes and positions using multiple active contour models (ACM’s). The algorithm or...
We propose a quasi-greedy algorithm for approximating the classical uncapacitated 2-level facility location problem (2-LFLP). Our algorithm, unlike the standard greedy algorithm, ...
The problem of computing a maximum a posteriori (MAP) configuration is a central computational challenge associated with Markov random fields. There has been some focus on “tr...
Pradeep Ravikumar, Alekh Agarwal, Martin J. Wainwr...
We propose an algorithm for the binarization of document images degraded by uneven light distribution, based on the Markov Random Field modeling with Maximum A Posteriori probabil...