| Distributionally Robust -Learning Z Liu, Q Bai, J Blanchet, P Dong, W Xu, Z Zhou, Z Zhou International Conference on Machine Learning, 13623-13643, 2022 | 51 | 2022 |
| High probability convergence of stochastic gradient methods Z Liu, TD Nguyen, TH Nguyen, A Ene, H Nguyen International Conference on Machine Learning, 21884-21914, 2023 | 39 | 2023 |
| Stochastic nonsmooth convex optimization with heavy-tailed noises Z Liu, Z Zhou arXiv preprint arXiv:2303.12277, 2023 | 16 | 2023 |
| On the Convergence of AdaGrad (Norm) on $\R^{d} $: Beyond Convexity, Non-Asymptotic Rate and Acceleration Z Liu, TD Nguyen, A Ene, HL Nguyen arXiv preprint arXiv:2209.14827, 2022 | 13 | 2022 |
| Breaking the lower bound with (little) structure: Acceleration in non-convex stochastic optimization with heavy-tailed noise Z Liu, J Zhang, Z Zhou The Thirty Sixth Annual Conference on Learning Theory, 2266-2290, 2023 | 12 | 2023 |
| Revisiting the last-iterate convergence of stochastic gradient methods Z Liu, Z Zhou arXiv preprint arXiv:2312.08531, 2023 | 9 | 2023 |
| Adaptive accelerated (extra-) gradient methods with variance reduction Z Liu, TD Nguyen, A Ene, H Nguyen International Conference on Machine Learning, 13947-13994, 2022 | 8 | 2022 |
| META-STORM: Generalized fully-adaptive variance reduced SGD for unbounded functions Z Liu, TD Nguyen, TH Nguyen, A Ene, HL Nguyen arXiv preprint arXiv:2209.14853, 2022 | 6 | 2022 |
| On the Last-Iterate Convergence of Shuffling Gradient Methods Z Liu, Z Zhou arXiv preprint arXiv:2403.07723, 2024 | 2 | 2024 |
| Near-Optimal Non-Convex Stochastic Optimization under Generalized Smoothness Z Liu, S Jagabathula, Z Zhou arXiv preprint arXiv:2302.06032, 2023 | 2 | 2023 |
