# New paper on compressive sensing

décembre, 3, 2009
Sylvain

Together with Alexandre Borghi and Jérome Darbon, we wrote a paper entitled Exact Optimization for the $l^1$-Compressive Sensing problem using a Modified Dantzig-Wolfe method.

the paper is available as a UCLA CAM Report here: cam09-101.pdf

Here is the abstract:
This paper considers the $l^1$-Compressive Sensing problem and presents an efficient algorithm that computes an exact solution. The idea consists in reformulating the problem such that it yields a modified Dantzig-Wolfe decomposition that allows to efficiently apply all standard simplex pivoting rules. Experimental results show the superiority of our approach compared to standard linear programming methods.