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Compressed Sensing - Introduction and Future Aspects

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If you have a question about this talk, please contact Richard Samworth.

Compressed Sensing is a remarkable tool for complete data reconstruction from highly under sampled data sets with applications in Medical Imaging, Image Reconstruction, Signal Processing etc. I will cover the basics from a non-technical point of view with emphasis on applications and statistical ideas. I will also discuss some of the limitations in the current theory and how to possibly handle much more general inverse problems in the future.

Preliminary reading:

A good survey for non-experts

A slightly more technical choice

For the advanced reader 1

For the advanced reader 2

This talk is part of the Statistics Reading Group series.

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