- Megasthenis Asteris, Dimitris S. Papailiopoulos, George N. Karystinos, “The Sparse Principal Component of a Constant-Rank Matrix”, IEEE Trans. Inform. Theory, 60, no. 4, 2014, 2281
- Yingtong Chen, Jigen Peng, Shigang Yue, “Preconditioning for Orthogonal Matching Pursuit with Noisy and Random Measurements: The Gaussian Case”, Circuits Syst Signal Process, 37, no. 9, 2018, 4109
- Olga Permiakova, Thomas Burger, “Sketched Stochastic Dictionary Learning for large‐scale data and application to high‐throughput mass spectrometry”, Statistical Analysis, 15, no. 1, 2022, 43
- Jaweria Amjad, Zhaoyan Lyu, Miguel R. D. Rodrigues, “Deep Learning Model-Aware Regulatization With Applications to Inverse Problems”, IEEE Trans. Signal Process., 69, 2021, 6371
- Andreu Cecilia, Ramon Costa-Castello, 2021 60th IEEE Conference on Decision and Control (CDC), 2021, 3996
- Wen-Zhi Sun, Zhen-Chun Li, Ying-Ming Qu, Zhi-Na Li, “Multiple attenuation using λ-f domain high-order and high-resolution Radon transform based on SL0 norm”, Appl. Geophys., 16, no. 4, 2019, 473
- Mostafa Sadeghi, Massoud Babaie-Zadeh, “Iterative Sparsification-Projection: Fast and Robust Sparse Signal Approximation”, IEEE Trans. Signal Process., 64, no. 21, 2016, 5536
- Shiqing Wang, Limin Su, “Recovery of High-Dimensional Sparse Signals via -Minimization”, Journal of Applied Mathematics, 2013, 2013, 1
- Saishang Zhong, Zhong Xie, Jinqin Liu, Zheng Liu, “Robust Mesh Denoising via Triple Sparsity”, Sensors, 19, no. 5, 2019, 1001
- M. Haddou, T. Migot, “A smoothing method for sparse optimization over convex sets”, Optim Lett, 14, no. 5, 2020, 1053