Winter Conference in Statistics 2013

Compressed Sensing - Theory and Applications

Compressed sensing (CS) is an exciting and rapidly growing field that has attracted considerable attentions in signal processing, statistics, applied mathematics, computer science, as well as the broader scientific community. Since its initial introduction only a few years ago, an avalanche of results has been obtained, both of theoretical and practical nature. CS offers a framework for simultaneous sensing and compression of finite-dimensional vectors that relies on linear dimensionality reduction. It predicts that sparse high-dimensional signals can be recovered from highly incomplete measurements by using efficient algorithms.

The speakers at this conference will provide our participants a comprehensive introduction to the subject, highlighting recent theoretical advances and a range of applications, as well as outlining numerous remaining research challenges.


Holger Rauhut, University of Bonn, and Department of Mathematics at RWTH Aachen University from March 1, 2013

Volkan Cevher, EPFL - École polytechnique fédérale de Lausanne


Hotel Borgafjäll, Box 46, 91704 Borgafjäll. Tel 0942-42100.


March 3-7, 2013

The participants are welcome to present posters on any topic and contributed talks related to the topic.


Swedish Statistical Society

Page Editor: Robert Johansson

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