Compressed Sensing and its Applications

1. On the Global-Local Dichotomy in Sparsity Modeling
Dmitry Batenkov, Yaniv Romano, Michael Elad

2. Fourier Phase Retrieval: Uniqueness and Algorithms
Tamir Bendory, Robert Beinert, Yonina C. Eldar

3. Compressed Sensing Approaches for Polynomial Approximation of High-Dimensional Functions
Ben Adcock, Simone Brugiapaglia, Clayton G. Webster

4. Multisection in the Stochastic Block Model Using Semidefinite Programming
Naman Agarwal, Afonso S. Bandeira, Konstantinos Koiliaris, Alexandra Kolla

5. Recovering Signals with Unknown Sparsity in Multiple Dictionaries
Rizwan Ahmad, Philip Schniter

6. Compressive Classification and the Rare Eclipse Problem
Afonso S. Bandeira, Dustin G. Mixon, Benjamin Recht

7. Weak Phase Retrieval
Sara Botelho-Andrade, Peter G. Casazza, Dorsa Ghoreishi, Shani Jose, Janet C. Tremain

8. Cubatures on Grassmannians: Moments, Dimension Reduction, and Related Topics
Anna Breger, Martin Ehler, Manuel Gräf, Thomas Peter

9. A Randomized Tensor Train Singular Value Decomposition
Benjamin Huber, Reinhold Schneider, Sebastian Wolf

10. Versatile and Scalable Cosparse Methods for Physics-Driven Inverse Problems
Srđan Kitić, Siouar Bensaid, Laurent Albera, Nancy Bertin, Rémi Gribonval

11. Total Variation Minimization in Compressed Sensing
Felix Krahmer, Christian Kruschel, Michael Sandbichler

12. Compressed Sensing in Hilbert Spaces
Yann Traonmilin, Gilles Puy, Rémi Gribonval, Mike E. Davies

Avainsanat: Mathematics, Information and Communication, Circuits, Numerical Analysis, Signal, Image and Speech Processing, Coding and Information Theory, Linear and Multilinear Algebras, Matrix Theory, Computational Science and Engineering