Sparse Signal Recovery Using Iterative Proximal Projection
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Mikael Skoglund | Christian Jutten | Massoud Babaie-Zadeh | Fateme Ghayem | Mostafa Sadeghi | Saikat Chatterjee | C. Jutten | M. Skoglund | S. Chatterjee | M. Sadeghi | M. Babaie-zadeh | F. Ghayem
[1] S. Foucart,et al. Sparsest solutions of underdetermined linear systems via ℓq-minimization for 0 , 2009 .
[2] Scott T. Rickard,et al. Comparing Measures of Sparsity , 2008, IEEE Transactions on Information Theory.
[3] M. Lustig,et al. Compressed Sensing MRI , 2008, IEEE Signal Processing Magazine.
[4] Benar Fux Svaiter,et al. Convergence of descent methods for semi-algebraic and tame problems: proximal algorithms, forward–backward splitting, and regularized Gauss–Seidel methods , 2013, Math. Program..
[5] Trac D. Tran,et al. ICR: Iterative Convex Refinement for Sparse Signal Recovery Using Spike and Slab Priors , 2015, ArXiv.
[6] Heinz H. Bauschke,et al. Fixed-Point Algorithms for Inverse Problems in Science and Engineering , 2011, Springer Optimization and Its Applications.
[7] I. Daubechies,et al. An iterative thresholding algorithm for linear inverse problems with a sparsity constraint , 2003, math/0307152.
[8] Jian Wang,et al. Generalized Orthogonal Matching Pursuit , 2011, IEEE Transactions on Signal Processing.
[9] Masoumeh Azghani. Iterative methods for random sampling and compressed sensing recovery , 2013 .
[10] R. Tibshirani. Regression Shrinkage and Selection via the Lasso , 1996 .
[11] Volkan Cevher,et al. Learning with Compressible Priors , 2009, NIPS.
[12] Patrick L. Combettes,et al. Proximal Splitting Methods in Signal Processing , 2009, Fixed-Point Algorithms for Inverse Problems in Science and Engineering.
[13] Jianqing Fan,et al. Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties , 2001 .
[14] Marc Teboulle,et al. A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems , 2009, SIAM J. Imaging Sci..
[15] Tong Zhang,et al. Analysis of Multi-stage Convex Relaxation for Sparse Regularization , 2010, J. Mach. Learn. Res..
[16] E.J. Candes,et al. An Introduction To Compressive Sampling , 2008, IEEE Signal Processing Magazine.
[17] P. Tseng. Convergence of a Block Coordinate Descent Method for Nondifferentiable Minimization , 2001 .
[18] Philip Schniter,et al. Expectation-Maximization Gaussian-Mixture Approximate Message Passing , 2012, IEEE Transactions on Signal Processing.
[19] Stephen P. Boyd,et al. Proximal Algorithms , 2013, Found. Trends Optim..
[20] Marc Teboulle,et al. Proximal alternating linearized minimization for nonconvex and nonsmooth problems , 2014, Math. Program..
[21] 慧 廣瀬. A Mathematical Introduction to Compressive Sensing , 2015 .
[22] Hédy Attouch,et al. On the convergence of the proximal algorithm for nonsmooth functions involving analytic features , 2008, Math. Program..
[23] Yonina C. Eldar,et al. Structured Compressed Sensing: From Theory to Applications , 2011, IEEE Transactions on Signal Processing.
[24] Holger Rauhut,et al. A Mathematical Introduction to Compressive Sensing , 2013, Applied and Numerical Harmonic Analysis.
[25] Wotao Yin,et al. A Block Coordinate Descent Method for Regularized Multiconvex Optimization with Applications to Nonnegative Tensor Factorization and Completion , 2013, SIAM J. Imaging Sci..
[26] Michael A. Saunders,et al. Atomic Decomposition by Basis Pursuit , 1998, SIAM J. Sci. Comput..
[27] Stéphane Canu,et al. Ieee Transactions on Signal Processing 1 Recovering Sparse Signals with a Certain Family of Non-convex Penalties and Dc Programming , 2022 .
[28] Massoud Babaie-Zadeh,et al. Successive Concave Sparsity Approximation for Compressed Sensing , 2015, IEEE Transactions on Signal Processing.
[29] Stephen J. Wright,et al. Computational Methods for Sparse Solution of Linear Inverse Problems , 2010, Proceedings of the IEEE.
[30] Wotao Yin,et al. Iteratively reweighted algorithms for compressive sensing , 2008, 2008 IEEE International Conference on Acoustics, Speech and Signal Processing.
[31] Jian Zhang,et al. Image compressive sensing recovery using adaptively learned sparsifying basis via L0 minimization , 2014, Signal Process..
[32] Yurii Nesterov,et al. Introductory Lectures on Convex Optimization - A Basic Course , 2014, Applied Optimization.
[33] Panagiotis Kosmas,et al. Microwave Medical Imaging Based on Sparsity and an Iterative Method With Adaptive Thresholding , 2015, IEEE Transactions on Medical Imaging.
[34] Christian Jutten,et al. A Fast Approach for Overcomplete Sparse Decomposition Based on Smoothed $\ell ^{0}$ Norm , 2008, IEEE Transactions on Signal Processing.
[35] Wotao Yin,et al. A Globally Convergent Algorithm for Nonconvex Optimization Based on Block Coordinate Update , 2014, J. Sci. Comput..
[36] Mike E. Davies,et al. Iterative Hard Thresholding for Compressed Sensing , 2008, ArXiv.
[37] D K Smith,et al. Numerical Optimization , 2001, J. Oper. Res. Soc..
[38] J. Friedman. Fast sparse regression and classification , 2012 .
[39] W. H. Young. On Classes of Summable Functions and their Fourier Series , 1912 .
[40] Massoud Babaie-Zadeh,et al. Iterative Sparsification-Projection: Fast and Robust Sparse Signal Approximation , 2016, IEEE Transactions on Signal Processing.
[41] T. Blumensath,et al. Theory and Applications , 2011 .