- Daniel Studer, Ulrich Hoffmann, Thomas Koenig, “From EEG dependency multichannel matching pursuit to sparse topographic EEG decomposition”, Journal of Neuroscience Methods, 153, № 2, 2006, 261
- Shan Luo, “Variable selection in high-dimensional sparse multiresponse linear regression models”, Stat Papers, 61, № 3, 2020, 1245
- A. Çivril, M. Magdon-Ismail, “Column subset selection via sparse approximation of SVD”, Theoretical Computer Science, 421, 2012, 1
- Q. Barthelemy, A. Larue, A. Mayoue, D. Mercier, J. I. Mars, 2011 IEEE Statistical Signal Processing Workshop (SSP), 2011, 645
- Jeffrey D. Blanchard, Michael Cermak, David Hanle, Yirong Jing, “Greedy Algorithms for Joint Sparse Recovery”, IEEE Trans. Signal Process., 62, № 7, 2014, 1694
- R.M. Figueras i Ventura, P. Vandergheynst, P. Frossard, A. Cavallaro, 3, 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2004, iii
- Xu Xu, Jinyu Guo, Peixin Ye, Wenhui Zhang, “Approximation Properties of the Vector Weak Rescaled Pure Greedy Algorithm”, Mathematics, 11, № 9, 2023, 2020
- Joel A. Tropp, Anna C. Gilbert, Martin J. Strauss, “Algorithms for simultaneous sparse approximation. Part I: Greedy pursuit”, Signal Processing, 86, № 3, 2006, 572
- Jeffrey D. Blanchard, Caleb Leedy, Yimin Wu, “On rank awareness, thresholding, and MUSIC for joint sparse recovery”, Applied and Computational Harmonic Analysis, 48, № 1, 2020, 482
- Jeffrey D. Blanchard, Jared Tanner, Ke Wei, “CGIHT: conjugate gradient iterative hard thresholding for compressed sensing and matrix completion”, Information and Inference, 2015, iav011