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MIA Talks

CS2: Compressed sensing

September 21, 2015
Broad Institute; Analytic and Translational Genetics Unit, Massachusetts General Hospital

How many linear measurements (equations) do you need to recover a high-dimensional signal (unknowns)? If you know a basis in which the signal is sparse, and your measurements are not too aligned with this basis, then far fewer than you might expect. Moreover, you can recast your underdetermined problem as a convex program and solve it efficiently. I will talk about when and why this works, mentioning some now-classic applications and a few exciting possibilities in biology.