The Fisher metric and sharp recovery bounds for multivariate off-the-grid compressed sensing

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• Clarice Poon, Lectrurer, University of Bath
• Tuesday 15 October 2019, 14:00-15:00
• Room 909B, EEE Building.

If you have a question about this talk, please contact Wei Dai.

Abstract: I will present an analysis of a continuous version of the compressed sensing problem, where the l^1 norm is replaced by the total variation of measures, and one aims to recover the positions and amplitudes of Dirac masses. We show that provided that the Diracs are sufficiently separated under a Fisher metric (which accounts for the geometry of the problem), stable recovery can be achieved when the number of random samples scales linearly with sparsity (up to log factors).

Short Bio: I completed my PhD at the Cambridge Centre for Analysis, University of Cambridge under the supervision of Anders Hansen. After my PhD, I took up a research fellowship at Peterhouse, Cambridge, and since December 2018, I have been a lecturer at the University of Bath.

This talk is part of the COMMSP Seminar series.

This talk is included in these lists:

• COMMSP & CP list
• COMMSP Seminar
• Room 909B, EEE Building
• SAP Talks

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