We study sparse principal components analysis in the high-dimensional setting, where p (the number of variables) can be much larger than n (the number of observations). We prove o...
Abstract. This paper presents a surveillance system for tracking multiple people through a wide area with sparsely distributed cameras. The computational core of the system is an a...
Wojciech Zajdel, Ali Taylan Cemgil, Ben J. A. Kr&o...
In this paper, we present an optimization framework for transmitting high quality audio sequences over error-prone wireless links. Our framework introduces apparatus and technique ...
Sparse signal representations and approximations from overcomplete dictionaries have become an invaluable tool recently. In this paper, we develop a new, heuristic, graph-structure...
Consider the decomposition of a signal into features that undergo transformations drawn from a continuous family. Current methods discretely sample the transformations and apply s...
Chaitanya Ekanadham, Daniel Tranchina, Eero P. Sim...