| Global optimality in low-rank matrix optimization Z Zhu, Q Li, G Tang, MB Wakin IEEE Transactions on Signal Processing 66 (13), 3614 - 3628, 2018 | 173 | 2018 |
| The nonconvex geometry of low-rank matrix optimization Q Li, Z Zhu, G Tang Information and Inference: A Journal of the IMA 8 (1), 51-96, 2018 | 144* | 2018 |
| Handbook of robust low-rank and sparse matrix decomposition: Applications in image and video processing T Bouwmans, NS Aybat, E Zahzah Chapman and Hall/CRC, 2016 | 135 | 2016 |
| JFB: Jacobian-free backpropagation for implicit networks SW Fung, H Heaton, Q Li, D McKenzie, S Osher, W Yin Proceedings of the AAAI Conference on Artificial Intelligence, 2022 | 124* | 2022 |
| The global optimization geometry of low-rank matrix optimization Z Zhu, Q Li, G Tang, MB Wakin IEEE Transactions on Information Theory 67 (2), 1308-1331, 2021 | 114* | 2021 |
| Alternating optimization of sensing matrix and sparsifying dictionary for compressed sensing H Bai, G Li, S Li, Q Li, Q Jiang, L Chang IEEE Transactions on Signal Processing 63 (6), 1581-1594, 2015 | 69 | 2015 |
| Alternating minimizations converge to second-order optimal solutions Q Li, Z Zhu, G Tang International Conference on Machine Learning, 3935-3943, 2019 | 64 | 2019 |
| Approximate support recovery of atomic line spectral estimation: A tale of resolution and precision Q Li, G Tang Applied and Computational Harmonic Analysis 48 (3), 891-948, 2020 | 52 | 2020 |
| Dropping symmetry for fast symmetric nonnegative matrix factorization Z Zhu, X Li, K Liu, Q Li Proceedings of the 32nd International Conference on Neural Information …, 2018 | 49 | 2018 |
| Geometry of factored nuclear norm regularization Q Li, Z Zhu, G Tang arXiv preprint arXiv:1704.01265, 2017 | 34 | 2017 |
| Provable Bregman-divergence based methods for nonconvex and non-Lipschitz problems Q Li, Z Zhu, G Tang, MB Wakin arXiv preprint arXiv:1904.09712, 2019 | 32 | 2019 |
| Optimized structured sparse sensing matrices for compressive sensing T Hong, X Li, Z Zhu, Q Li Signal processing 159, 119-129, 2019 | 30 | 2019 |
| Learn to predict equilibria via fixed point networks H Heaton, D McKenzie, Q Li, SW Fung, S Osher, W Yin arXiv preprint arXiv:2106.00906 3, 2021 | 28 | 2021 |
| Distributed low-rank matrix factorization with exact consensus Z Zhu, Q Li, X Yang, G Tang, MB Wakin Advances in Neural Information Processing Systems 32, 2019 | 23* | 2019 |
| Overcomplete tensor decomposition via convex optimization Q Li, A Prater, L Shen, G Tang 2015 IEEE 6th International Workshop on Computational Advances in Multi …, 2015 | 23 | 2015 |
| The global geometry of centralized and distributed low-rank matrix recovery without regularization S Li, Q Li, Z Zhu, G Tang, MB Wakin IEEE Signal Processing Letters 27, 1400-1404, 2020 | 21 | 2020 |
| Spherical principal component analysis K Liu, Q Li, H Wang, G Tang Proceedings of the 2019 SIAM international conference on data mining, 387-395, 2019 | 16 | 2019 |
| A provable splitting approach for symmetric nonnegative matrix factorization X Li, Z Zhu, Q Li, K Liu IEEE Transactions on Knowledge and Data Engineering 35 (3), 2206-2219, 2021 | 15 | 2021 |
| On collaborative compressive sensing systems: The framework, design, and algorithm Z Zhu, G Li, J Ding, Q Li, X He SIAM Journal on imaging sciences 11 (2), 1717-1758, 2018 | 14 | 2018 |
| From the simplex to the sphere: faster constrained optimization using the Hadamard parametrization Q Li, D McKenzie, W Yin Information and Inference: A Journal of the IMA 12 (3), 1898-1937, 2023 | 13 | 2023 |
Gongguo TangAssociate Professor, University of Colorado Boulder在 Colorado.edu 的电子邮件经过验证
