New paper on compressive sensing

décembre, 3, 2009

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.

Comments are more than welcome!

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Picture: courtesy of Abby Blank