On layer normalization in the transformer architecture R Xiong, Y Yang, D He, K Zheng, S Zheng, C Xing, H Zhang, Y Lan, ...
International conference on machine learning, 10524-10533, 2020
1143 2020 Differentially private fine-tuning of language models D Yu, S Naik, A Backurs, S Gopi, HA Inan, G Kamath, J Kulkarni, YT Lee, ...
arXiv preprint arXiv:2110.06500, 2021
355 2021 A nonconvex approach for phase retrieval: Reshaped wirtinger flow and incremental algorithms H Zhang, Y Liang, Y Chi
Journal of Machine Learning Research 18 (141), 1-35, 2017
329 * 2017 Provable non-convex phase retrieval with outliers: Median truncatedwirtinger flow H Zhang, Y Chi, Y Liang
International conference on machine learning, 1022-1031, 2016
160 * 2016 Do not let privacy overbill utility: Gradient embedding perturbation for private learning D Yu, H Zhang, W Chen, TY Liu
arXiv preprint arXiv:2102.12677, 2021
118 2021 Large scale private learning via low-rank reparametrization D Yu, H Zhang, W Chen, J Yin, TY Liu
International Conference on Machine Learning, 12208-12218, 2021
107 2021 Block-diagonal hessian-free optimization for recurrent and convolutional neural networks H Zhang, C Xiong
US Patent 11,386,327, 2022
103 * 2022 Sgd converges to global minimum in deep learning via star-convex path Y Zhou, J Yang, H Zhang, Y Liang, V Tarokh
arXiv preprint arXiv:1901.00451, 2019
82 2019 Availability attacks create shortcuts D Yu, H Zhang, W Chen, J Yin, TY Liu
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022
77 * 2022 Adaptive inertia: Disentangling the effects of adaptive learning rate and momentum Z Xie, X Wang, H Zhang, I Sato, M Sugiyama
International conference on machine learning, 24430-24459, 2022
69 * 2022 How does data augmentation affect privacy in machine learning? D Yu, H Zhang, W Chen, J Yin, TY Liu
Proceedings of the AAAI conference on artificial intelligence 35 (12), 10746 …, 2021
63 2021 Convergence of adagrad for non-convex objectives: Simple proofs and relaxed assumptions B Wang, H Zhang, Z Ma, W Chen
The Thirty Sixth Annual Conference on Learning Theory, 161-190, 2023
59 2023 Understanding generalization error of SGD in nonconvex optimization Y Zhou, Y Liang, H Zhang
Machine Learning, 1-31, 2022
57 * 2022 Provable adaptivity of adam under non-uniform smoothness B Wang, Y Zhang, H Zhang, Q Meng, R Sun, ZM Ma, TY Liu, ZQ Luo, ...
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and …, 2024
49 2024 Exploring the limits of differentially private deep learning with group-wise clipping J He, X Li, D Yu, H Zhang, J Kulkarni, YT Lee, A Backurs, N Yu, J Bian
arXiv preprint arXiv:2212.01539, 2022
47 2022 Gradient perturbation is underrated for differentially private convex optimization D Yu, H Zhang, W Chen, TY Liu, J Yin
arXiv preprint arXiv:1911.11363, 2019
45 2019 Normalized/clipped sgd with perturbation for differentially private non-convex optimization X Yang, H Zhang, W Chen, TY Liu
arXiv preprint arXiv:2206.13033, 2022
38 2022 Non-convex low-rank matrix recovery with arbitrary outliers via median-truncated gradient descent Y Li, Y Chi, H Zhang, Y Liang
Information and Inference: A Journal of the IMA 9 (2), 289-325, 2020
34 2020 Q Meng, S Zheng, H Zhang, W Chen, ZM Ma, TY Liu
arXiv preprint arXiv:1802.03713, 2018
34 2018 Stabilize deep ResNet with a sharp scaling factor H Zhang, D Yu, M Yi, W Chen, TY Liu
Machine Learning 111 (9), 3359-3392, 2022
33 * 2022 
Tie-Yan LiuPresident, Zhongguancun Academy | IEEE Fellow | ACM Fellow | AAIA FellowEmail được xác minh tại bjzgca.edu.cn