Data-driven diagnosis for compressed sensing algorithms

[1]  Andrea Montanari,et al.  Message-passing algorithms for compressed sensing , 2009, Proceedings of the National Academy of Sciences.

[2]  J. Tropp,et al.  CoSaMP: Iterative signal recovery from incomplete and inaccurate samples , 2008, Commun. ACM.

[3]  Joel A. Tropp,et al.  Living on the edge: phase transitions in convex programs with random data , 2013, 1303.6672.

[4]  Simon Foucart,et al.  Hard Thresholding Pursuit: An Algorithm for Compressive Sensing , 2011, SIAM J. Numer. Anal..

[5]  Kazunori Akiyama,et al.  Super-resolution imaging with radio interferometry using sparse modeling , 2014, 1407.2422.

[6]  B. Efron,et al.  A Leisurely Look at the Bootstrap, the Jackknife, and , 1983 .

[7]  L. Gladden,et al.  Fast multidimensional NMR spectroscopy using compressed sensing. , 2011, Angewandte Chemie.

[8]  Joel A. Tropp,et al.  Sharp Recovery Bounds for Convex Demixing, with Applications , 2012, Found. Comput. Math..

[9]  E.J. Candes,et al.  An Introduction To Compressive Sampling , 2008, IEEE Signal Processing Magazine.

[10]  J. Claerbout,et al.  Robust Modeling With Erratic Data , 1973 .

[11]  T. Blumensath,et al.  Iterative Thresholding for Sparse Approximations , 2008 .

[12]  Emmanuel J. Candès,et al.  Exact Matrix Completion via Convex Optimization , 2009, Found. Comput. Math..

[13]  O. Katz,et al.  Compressive ghost imaging , 2009, 0905.0321.

[14]  Pablo A. Parrilo,et al.  Guaranteed Minimum-Rank Solutions of Linear Matrix Equations via Nuclear Norm Minimization , 2007, SIAM Rev..

[15]  Kazunori Akiyama,et al.  PRECL: A new method for interferometry imaging from closure phase , 2016, 1603.07078.

[16]  H. Nishimori Statistical Physics of Spin Glasses and Information Processing , 2001 .

[17]  H. L. Taylor,et al.  Deconvolution with the l 1 norm , 1979 .

[18]  Emmanuel J. Candès,et al.  Decoding by linear programming , 2005, IEEE Transactions on Information Theory.

[19]  R. Tibshirani Regression Shrinkage and Selection via the Lasso , 1996 .

[20]  Antonin Chambolle,et al.  A First-Order Primal-Dual Algorithm for Convex Problems with Applications to Imaging , 2011, Journal of Mathematical Imaging and Vision.

[21]  Mike E. Davies,et al.  Iterative Hard Thresholding for Compressed Sensing , 2008, ArXiv.

[22]  Y. C. Pati,et al.  Orthogonal matching pursuit: recursive function approximation with applications to wavelet decomposition , 1993, Proceedings of 27th Asilomar Conference on Signals, Systems and Computers.

[23]  Sheng Chen,et al.  Orthogonal least squares methods and their application to non-linear system identification , 1989 .

[24]  Olgica Milenkovic,et al.  Subspace Pursuit for Compressive Sensing Signal Reconstruction , 2008, IEEE Transactions on Information Theory.

[25]  M. Lustig,et al.  Compressed Sensing MRI , 2008, IEEE Signal Processing Magazine.

[26]  Wenlin Gong,et al.  Ghost imaging lidar via sparsity constraints , 2012, 1203.3835.

[27]  V. Orekhov,et al.  Accelerated NMR spectroscopy by using compressed sensing. , 2011, Angewandte Chemie.

[28]  D. Donoho,et al.  Sparse MRI: The application of compressed sensing for rapid MR imaging , 2007, Magnetic resonance in medicine.

[29]  C. I. Mosier I. Problems and Designs of Cross-Validation 1 , 1951 .

[30]  M. R. Osborne,et al.  A new approach to variable selection in least squares problems , 2000 .

[31]  D. Donoho,et al.  Atomic Decomposition by Basis Pursuit , 2001 .

[32]  Wotao Yin,et al.  Bregman Iterative Algorithms for (cid:2) 1 -Minimization with Applications to Compressed Sensing ∗ , 2008 .