| Toward understanding the importance of noise in training neural networks M Zhou, T Liu, Y Li, D Lin, E Zhou, T Zhao International Conference on Machine Learning, 7594-7602, 2019 | 91 | 2019 |
| Explicit convergence rates of greedy and random quasi-Newton methods D Lin, H Ye, Z Zhang Journal of Machine Learning Research 23 (162), 1-40, 2022 | 19 | 2022 |
| Greedy and random quasi-newton methods with faster explicit superlinear convergence D Lin, H Ye, Z Zhang Advances in Neural Information Processing Systems 34, 6646-6657, 2021 | 16 | 2021 |
| Towards explicit superlinear convergence rate for SR1 H Ye, D Lin, X Chang, Z Zhang Mathematical Programming 199 (1-2), 1273-1303, 2023 | 10 | 2023 |
| Explicit superlinear convergence rates of Broyden's methods in nonlinear equations D Lin, H Ye, Z Zhang arXiv preprint arXiv:2109.01974, 2021 | 9 | 2021 |
| Stochastic Distributed Optimization under Average Second-order Similarity: Algorithms and Analysis D Lin, Y Han, H Ye, Z Zhang Advances in Neural Information Processing Systems 36, 2024 | 8 | 2024 |
| Greedy and random Broyden's methods with explicit superlinear convergence rates in nonlinear equations H Ye, D Lin, Z Zhang arXiv preprint arXiv:2110.08572, 2021 | 8 | 2021 |
| Explicit superlinear convergence rates of the SR1 algorithm H Ye, D Lin, Z Zhang, X Chang arXiv preprint arXiv:2105.07162, 2021 | 7 | 2021 |
| On the landscape of one-hidden-layer sparse networks and beyond D Lin, R Sun, Z Zhang Artificial Intelligence 309, 103739, 2022 | 5 | 2022 |
| Faster directional convergence of linear neural networks under spherically symmetric data D Lin, R Sun, Z Zhang Advances in Neural Information Processing Systems 34, 4647-4660, 2021 | 4 | 2021 |
| Optimal quantization for batch normalization in neural network deployments and beyond D Lin, P Sun, G Xie, S Zhou, Z Zhang arXiv preprint arXiv:2008.13128, 2020 | 4 | 2020 |
| Global convergence analysis of deep linear networks with a one-neuron layer K Chen, D Lin, Z Zhang arXiv preprint arXiv:2201.02761, 2022 | 2 | 2022 |
| Towards better generalization: Bp-svrg in training deep neural networks H Jin, D Lin, Z Zhang arXiv preprint arXiv:1908.06395, 2019 | 2 | 2019 |
| On Non-local Convergence Analysis of Deep Linear Networks K Chen, D Lin, Z Zhang International Conference on Machine Learning, 3417-3443, 2022 | 1 | 2022 |
| Anderson Acceleration Without Restart: A Novel Method with -Step Super Quadratic Convergence Rate H Ye, D Lin, X Chang, Z Zhang arXiv preprint arXiv:2403.16734, 2024 | | 2024 |
| On the Convergence of Policy in Unregularized Policy Mirror Descent D Lin, Z Zhang arXiv preprint arXiv:2205.08176, 2022 | | 2022 |
| Meta-Regularization: An Approach to Adaptive Choice of the Learning Rate in Gradient Descent G Xie, H Jin, D Lin, Z Zhang arXiv preprint arXiv:2104.05447, 2021 | | 2021 |
Zhihua ZhangProfessor of Computer Science, Shanghai Jiao Tong University在 zju.edu.cn 的电子邮件经过验证
