| Convergence properties of the randomized extended Gauss--Seidel and Kaczmarz methods A Ma, D Needell, A Ramdas SIAM Journal on Matrix Analysis and Applications 36 (4), 1590-1604, 2015 | 181 | 2015 |
| Greed works: An improved analysis of sampling Kaczmarz--Motzkin J Haddock, A Ma SIAM Journal on Mathematics of Data Science 3 (1), 342-368, 2021 | 45 | 2021 |
| Stochastic gradient descent for linear systems with missing data A Ma, D Needell arXiv preprint arXiv:1702.07098, 2017 | 23 | 2017 |
| An approximate message passing framework for side information A Ma, Y Zhou, C Rush, D Baron, D Needell IEEE Transactions on Signal Processing 67 (7), 1875-1888, 2019 | 19 | 2019 |
| Unsupervised record matching with noisy and incomplete data Y van Gennip, B Hunter, A Ma, D Moyer, R de Vera, AL Bertozzi International Journal of Data Science and Analytics 6, 109-129, 2018 | 18 | 2018 |
| Randomized Kaczmarz for tensor linear systems A Ma, D Molitor BIT Numerical Mathematics 62 (1), 171-194, 2022 | 16 | 2022 |
| Iterative methods for solving factorized linear systems A Ma, D Needell, A Ramdas SIAM Journal on Matrix Analysis and Applications 39 (1), 104-122, 2018 | 15 | 2018 |
| Iterative hard thresholding for low cp-rank tensor models R Grotheer, S Li, A Ma, D Needell, J Qin arXiv preprint arXiv:1908.08479, 2019 | 10 | 2019 |
| Stochastic greedy algorithms for multiple measurement vectors J Qin, S Li, D Needell, A Ma, R Grotheer, C Huang, N Durgin arXiv preprint arXiv:1711.01521, 2017 | 9 | 2017 |
| Sparse randomized kaczmarz for support recovery of jointly sparse corrupted multiple measurement vectors N Durgin, R Grotheer, C Huang, S Li, A Ma, D Needell, J Qin Research in Data Science, 1-14, 2019 | 8 | 2019 |
| Improving image clustering using sparse text and the wisdom of the crowds A Ma, A Flenner, D Needell, AG Percus 2014 48th Asilomar Conference on Signals, Systems and Computers, 1555-1557, 2014 | 7 | 2014 |
| Analysis of fast structured dictionary learning S Ravishankar, A Ma, D Needell Information and Inference: A Journal of the IMA 9 (4), 785-811, 2020 | 6 | 2020 |
| Fast hyperspectral diffuse optical imaging method with joint sparsity N Durgin, R Grotheer, C Huang, S Li, A Ma, D Needell, J Qin 2019 41st Annual International Conference of the IEEE Engineering in …, 2019 | 6 | 2019 |
| Stochastic greedy algorithms for multiple measurement vectors J Qin, S Li, D Needell, A Ma, R Grotheer, C Huang, N Durgin Inverse Problems & Imaging 15 (1), 2021 | 5 | 2021 |
| Stochastic iterative hard thresholding for low-Tucker-rank tensor recovery R Grotheer, S Li, A Ma, D Needell, J Qin 2020 Information Theory and Applications Workshop (ITA), 1-5, 2020 | 5 | 2020 |
| Conditional approximate message passing with side information D Baron, A Ma, D Needell, C Rush, T Woolf 2017 51st Asilomar Conference on Signals, Systems, and Computers, 430-434, 2017 | 5 | 2017 |
| A gradient descent approach for incomplete linear systems A Ma, D Needell 2018 52nd Asilomar Conference on Signals, Systems, and Computers, 764-768, 2018 | 3 | 2018 |
| Compressed anomaly detection with multiple mixed observations N Durgin, R Grotheer, C Huang, S Li, A Ma, D Needell, J Qin Research in Data Science, 211-237, 2019 | 2 | 2019 |
| Analysis of fast alternating minimization for structured dictionary learning S Ravishankar, A Ma 2018 Information Theory and Applications Workshop (ITA), 1-9, 2018 | 2 | 2018 |
| Robust recovery of low-rank matrices and low-tubal-rank tensors from noisy sketches A Ma, D Stöger, Y Zhu SIAM Journal on Matrix Analysis and Applications 44 (4), 1566-1588, 2023 | 1 | 2023 |
