| Communication-efficient algorithms for decentralized and stochastic optimization G Lan, S Lee, Y Zhou Mathematical Programming 180 (1), 237-284, 2020 | 140 | 2020 |
| Reshaped Wirtinger Flow and Incremental Algorithms for Solving Quadratic Systems of Equations H Zhang, Y Zhou, Y Liang, Y Chi arXiv preprint, 0 | 103* | |
| Spiderboost: A class of faster variance-reduced algorithms for nonconvex optimization Z Wang, K Ji, Y Zhou, Y Liang, V Tarokh arXiv preprint arXiv:1810.10690 2 (3), 4, 2018 | 60 | 2018 |
| A nonconvex approach for phase retrieval: Reshaped wirtinger flow and incremental algorithms H Zhang, Y Zhou, Y Liang, Y Chi Journal of Machine Learning Research 18, 2017 | 58 | 2017 |
| Convergence analysis of proximal gradient with momentum for nonconvex optimization Q Li, Y Zhou, Y Liang, PK Varshney International Conference on Machine Learning, 2111-2119, 2017 | 46 | 2017 |
| SpiderBoost and momentum: Faster stochastic variance reduction algorithms Z Wang, K Ji, Y Zhou, Y Liang, V Tarokh arXiv preprint arXiv:1810.10690, 2018 | 29 | 2018 |
| Stochastic variance-reduced cubic regularization for nonconvex optimization Z Wang, Y Zhou, Y Liang, G Lan The 22nd International Conference on Artificial Intelligence and Statistics …, 2019 | 25 | 2019 |
| SGD Converges to Global Minimum in Deep Learning via Star-convex Path Y Zhou, J Yang, H Zhang, Y Liang, V Tarokh ICLR2019, 2018 | 25 | 2018 |
| Critical points of linear neural networks: Analytical forms and landscape properties Y Zhou, Y Liang ICLR2018, 2018 | 25 | 2018 |
| Reshaped Wirtinger flow and incremental algorithm for solving quadratic system of equations H Zhang, Y Zhou, Y Liang, Y Chi arXiv preprint arXiv:1605.07719, 2016 | 25 | 2016 |
| Improved zeroth-order variance reduced algorithms and analysis for nonconvex optimization K Ji, Z Wang, Y Zhou, Y Liang International Conference on Machine Learning, 3100-3109, 2019 | 24 | 2019 |
| Characterization of gradient dominance and regularity conditions for neural networks Y Zhou, Y Liang arXiv preprint arXiv:1710.06910, 2017 | 22 | 2017 |
| On convergence of model parallel proximal gradient algorithm for stale synchronous parallel system Y Zhou, Y Yu, W Dai, Y Liang, E Xing Artificial Intelligence and Statistics, 713-722, 2016 | 21 | 2016 |
| Distributed machine learning via sufficient factor broadcasting P Xie, JK Kim, Y Zhou, Q Ho, A Kumar, Y Yu, E Xing arXiv preprint arXiv:1511.08486, 2015 | 21 | 2015 |
| Towards taming the resource and data heterogeneity in federated learning Z Chai, H Fayyaz, Z Fayyaz, A Anwar, Y Zhou, N Baracaldo, H Ludwig, ... 2019 {USENIX} Conference on Operational Machine Learning (OpML 19), 19-21, 2019 | 17 | 2019 |
| Learning latent space models with angular constraints P Xie, Y Deng, Y Zhou, A Kumar, Y Yu, J Zou, EP Xing International Conference on Machine Learning, 3799-3810, 2017 | 16 | 2017 |
| Geometrical properties and accelerated gradient solvers of non-convex phase retrieval Y Zhou, H Zhang, Y Liang 2016 54th Annual Allerton Conference on Communication, Control, and …, 2016 | 16 | 2016 |
| Reanalysis of variance reduced temporal difference learning T Xu, Z Wang, Y Zhou, Y Liang arXiv preprint arXiv:2001.01898, 2020 | 15 | 2020 |
| Analysis of Robust PCA via Local Incoherence. H Zhang, Y Zhou, Y Liang NIPS, 1819-1827, 2015 | 13 | 2015 |
| Toward understanding the impact of staleness in distributed machine learning W Dai, Y Zhou, N Dong, H Zhang, EP Xing arXiv preprint arXiv:1810.03264, 2018 | 11 | 2018 |
Huishuai ZhangMicrosoft Research AsiaVerified email at microsoft.com
