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Huishuai Zhang
Huishuai Zhang
Microsoft Research Asia
Verified email at microsoft.com - Homepage
Title
Cited by
Cited by
Year
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
3132020
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
247*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
119*2016
Block-diagonal hessian-free optimization for recurrent and convolutional neural networks
H Zhang, C Xiong
US Patent 11,386,327, 2022
53*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
472019
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
432021
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
362021
Understanding generalization error of SGD in nonconvex optimization
Y Zhou, Y Liang, H Zhang
Machine Learning 111 (1), 345-375, 2022
28*2022
The capacity region of the source-type model for secret key and private key generation
H Zhang, L Lai, Y Liang, H Wang
IEEE Transactions on Information Theory 60 (10), 6389-6398, 2014
28*2014
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
252020
-SGD: Optimizing ReLU Neural Networks in its Positively Scale-Invariant Space
Q Meng, S Zheng, H Zhang, W Chen, ZM Ma, TY Liu
arXiv preprint arXiv:1802.03713, 2018
242018
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
232016
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
222019
Capacity control of ReLU neural networks by basis-path norm
S Zheng, Q Meng, H Zhang, W Chen, N Yu, TY Liu
Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 5925-5932, 2019
222019
Convergence of distributed stochastic variance reduced methods without sampling extra data
S Cen, H Zhang, Y Chi, W Chen, TY Liu
IEEE Transactions on Signal Processing 68, 3976-3989, 2020
212020
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
192021
Stabilize deep ResNet with a sharp scaling factor τ
H Zhang, D Yu, M Yi, W Chen, TY Liu
Machine Learning 111 (9), 3359-3392, 2022
18*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
172021
Multi-key generation over a cellular model with a helper
H Zhang, Y Liang, L Lai, SS Shitz
IEEE Transactions on Information Theory 63 (6), 3804-3822, 2017
17*2017
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
16*2022
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