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Huishuai Zhang

Assistant Professor
Peking University
zhanghuishuai (at) pku.edu.cn


About Me

Hello! This is Huishuai Zhang. I am an assistant professor at Wangxuan Institute of Computer Technology, Peking Universy starting from Jan. 2024. Before joining academia, I was a Principal Researcher at Microsoft Research Asia. Before that, I graduated from Syracuse University with Ph.D under the supervision of Prof. Yingbin Liang. My research work aims at understanding the fundamental limits of machine learning, designing efficient and robust learning algorithms.

Research Interests

News

We have opening positions for PhDs and Research Interns (not limited to PKU, work online). If you are interested, please contact me freely! 长期招收实习生（可远程校外实习, 申请2025年秋季入学博士/硕士的学生，建议先联系实习），如感兴趣请直接联系我！

Publications

PrePrints

  1. Provable Benefit of Adaptivity in Adam
    Bohan Wang, Yushun Zhang, Huishuai Zhang, Qi Meng, Zhi-Ming Ma, Tie-Yan Liu and Wei Chen
    ArXiv
  2. Normalized/clipped sgd with perturbation for differentially private non-convex optimization
    Xiaodong Yang, Huishuai Zhang, Wei Chen and Tie-Yan Liu
    ArXiv, submitted to TMLR

Conference Proceedings

  1. On the Generalization Properties of Diffusion Models
    Puheng Li, Zhong Li, Huishuai Zhang^*, Jiang Bian
    Conference on Neural Information Processing Systems (NeurIPS), 2023
  2. DiffKendall: A Novel Approach for Few-Shot Learning with Differentiable Kendall's Rank Correlation
    Kaipeng Zheng, Huishuai Zhang, Weiran Huang
    Conference on Neural Information Processing Systems (NeurIPS), 2023
  3. FD-Align: Feature Discrimination Alignment for Fine-tuning Pre-Trained Models in Few-Shot Learning
    Kun Song, Huimin Ma, Bochao Zou, Huishuai Zhang, Weiran Huang
    Conference on Neural Information Processing Systems (NeurIPS), 2023
  4. Large Catapults in Momentum Gradient Descent with Warmup: An Empirical Study
    Prin Phunyaphibarn, Junghyun Lee, Bohan Wang, Huishuai Zhang, Chulhee Yun
    NeurIPS 2023 Workshop on Mathematics of Modern Machine Learning (Oral)
  5. Closing the gap between the upper bound and lower bound of Adam's iteration complexity
    Bohan Wang, Jingwen Fu, Huishuai Zhang, Nanning Zheng, Wei Chen
    Conference on Neural Information Processing Systems (NeurIPS), 2023
  6. Convergence of AdaGrad for Non-convex Objectives: Simple Proofs and Relaxed Assumptions
    Bohan Wang, Huishuai Zhang, Zhi-Ming Ma, Wei Chen
    Conference on Learning Theory (COLT), 2023
  7. Exploring the Limits of Differentially Private Deep Learning with Group-wise Clipping
    Jiyan He, Xuechen Li, Da Yu, Huishuai Zhang, Janardhan Kulkarni, Yin Tat Lee, Arturs Backurs, Nenghai Yu, Jiang Bian
    International Conference on Learning Representations (ICLR), 2023
  8. Denoising Masked AutoEncoders are Certifiable Robust Vision Learners
    Quanlin Wu, Hang Ye, Yuntian Gu, Huishuai Zhang, Liwei Wang, Di He
    International Conference on Learning Representations (ICLR), 2023
  9. Adversarial Noises Are Linearly Separable for (Nearly) Random Neural Networks
    Huishuai Zhang, Da Yu, Yiping Lu, Di He
    AISTATS, 2023
  10. UADB: Unsupervised Anomaly Detection Booster
    Hangting Ye, Zhining Liu, Xinyi Shen, Wei Cao, Shun Zheng, Xiaofan Gui, Huishuai Zhang, Yi Chang, Jiang Bian
    ICDE, 2023
  11. Similarity Distribution based Membership Inference Attack on Person Re-identification
    Junyao Gao, Xinyang Jiang, Huishuai Zhang, Yifan Yang, Shuguang Dou, Dongsheng Li, Duoqian Miao, Cheng Den, Cairong Zhao
    AAAI, 2023
  12. Does Momentum Change the Implicit Regularization on Separable Data?
    Bohan Wang, Qi Meng, Huishuai Zhang, Ruoyu Sun, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu
    NeurIPS, 2022
  13. Adaptive inertia: Disentangling the effects of adaptive learning rate and momentum
    Zeke Xie, Xinrui Wang, Huishuai Zhang, Issei Sato, Masashi Sugiyama
    ICML, 2022
  14. Availability attacks create shortcuts
    Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu
    KDD, 2022
  15. Two Coupled Rejection Metrics Can Tell Adversarial Examples Apart
    Tianyu Pang, Huishuai Zhang, Di He, Yinpeng Dong, Hang Su, Wei Chen, Jun Zhu, Tie-Yan Liu
    CVPR, 2022
  16. Differentially private fine-tuning of language models
    Da Yu, Saurabh Naik, Arturs Backurs, Sivakanth Gopi, Huseyin A Inan, Gautam Kamath, Janardhan Kulkarni, Yin Tat Lee andre Manoel, Lukas Wutschitz, Sergey Yekhanin, Huishuai Zhang
    International Conference on Learning Representations (ICLR), 2022
  17. Optimizing Information-theoretical Generalization Bound via Anisotropic Noise of SGLD
    Bohan Wang, Huishuai Zhang, Jieyu Zhang, Qi Meng, Wei Chen, Tie-Yan Liu
    NeurIPS, 2021
  18. Large scale private learning via low-rank reparametrization
    Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu
    ICML, 2021
  19. Do not Let Privacy Overbill Utility: Gradient Embedding Perturbation for Private Learning
    Da Yu, Huishuai Zhang, Wei Chen, Tie-Yan Liu
    International Conference on Learning Representations (ICLR), 2021
  20. How Does Data Augmentation Affect Privacy in Machine Learning?
    Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu
    AAAI, 2021
  21. On Layer Normalization in the Transformer Architecture
    Ruibin Xiong, Yunchang Yang, Di He, Kai Zheng, Shuxin Zheng, Chen Xing, Huishuai Zhang, Yanyan Lan, Liwei Wang, Tie-Yan Liu
    ICML, 2020
  22. Gradient Perturbation is Underrated for Differentially Private Convex Optimization
    Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu
    IJCAI, 2020
  23. SGD Converges to Global Minimum in Deep Learning via Star-convex Path
    Yi Zhou, Junjie Yang, Huishuai Zhang, Yingbin Liang
    International Conference on Learning Representations (ICLR), 2019
  24. G-SGD: Optimizing ReLU Neural Networks in its Positively Scale-Invariant Space
    Qi Meng, Shuxin Zheng, Huishuai Zhang, Wei Chen, Qiwei Ye, Zhi-Ming Ma, Nenghai Yu, Tie-Yan Liu
    International Conference on Learning Representations (ICLR), 2019
  25. Capacity Control of ReLU Neural Networks by Basis-path Norm
    Qi Meng, Shuxin Zheng, Huishuai Zhang, Nenghai Yu, Tie-Yan Liu, Wei Chen
    AAAI Conference on Artificial Intelligence, 2019
  26. BN-invariant Sharpness Regularizes the Training Model to Better Generalization
    Mingyang Yi, Huishuai Zhang, Wei Chen, Zhiming Ma, Tie-Yan Liu
    IJCAI, 2019
  27. On the local Hessian in back-propagation
    Huishuai Zhang, Wei Chen, Tie-Yan Liu
    Neural Information Processing Systems (NeurIPS), December 2018
  28. Reshaped Wirtinger flow for solving quadratic system of equations
    Huishuai Zhang, Yingbin Liang
    Neural Information Processing System (NeurIPS), Barcelona, Spain, December 2016
  29. Accelerated method for solving quadratic system of equations
    Yi Zhou, Huishuai Zhang, Yingbin Liang
    Allerton Conference, Champaign, Illinois, September 2016
  30. On orthogonal compressive sensing
    Yi Zhou, Huishuai Zhang, Yingbin Liang
    Allerton Conference on Communication, Control and Computing, Champaign, Illinois, September 2016
  31. Provable non-convex phase retrieval with outliers: Median truncated Wirtinger flow
    Huishuai Zhang, Yuejie Chi, Yingbin Liang
    ICML, New York City, USA, June 2016
  32. Analysis of robust PCA via local incoherence
    Huishuai Zhang, Yi Zhou, Yingbin Liang
    Neural Information Processing Systems (NIPS), Montreal, Canada, December 2015
  33. Secret key capacity: Talk or keep silent?
    Huishuai Zhang, Yingbin Liang, Lifeng Lai
    Proc. IEEE International Symposium on Information Theory (ISIT), Hong Kong, China, June 2015
  34. Two-key generation for a cellular model with a helper
    Huishuai Zhang, Yingbin Liang, Lifeng Lai, Shlomo Shamai
    Proc. IEEE International Symposium on Information Theory (ISIT), Hong Kong, China, June 2015
  35. Key capacity region for a cellular source model
    Huishuai Zhang, Yingbin Liang, Lifeng Lai
    Proc. IEEE Information Theory Workshop (ITW), Hobart, Tasmania, Australia, November 2014
  36. Helper-assisted asymmetric two key generation
    Huishuai Zhang, Yingbin Liang, Lifeng Lai
    Proc. Asilomar Conference on Signals, Systems and Computers, Pacific Grove, CA, USA, November 2014
  37. The secret key-private key generation over three terminals: Capacity region
    Huishuai Zhang, Lifeng Lai, Yingbin Liang, Hua Wang
    Proc. IEEE International Symposium on Information Theory (ISIT), Honolulu, HI, USA, June 2014

Journals

  1. Stabilize Deep ResNet with A Sharp Scaling Factor τ
    Huishuai Zhang, Da Yu, Mingyang Yi, Wei Chen, Tie-Yan Liu
    Machine Learning, Springer, 2022
  2. Understanding generalization error of SGD in nonconvex optimization
    Yi Zhou, Yingbin Liang, Huishuai Zhang
    Machine Learning, Springer, 2022
  3. Convergence of Distributed Stochastic Variance Reduced Methods without Sampling Extra Data
    Shicong Cen, Huishuai Zhang, Yuejie Chi, Wei Chen, Tie-Yan Liu
    IEEE Transactions on Signal Processing, vol. 68, pp. 3976-3989, 2020
  4. Nonconvex Low-Rank Matrix Recovery with Arbitrary Outliers via Median-Truncated Gradient Descent
    Yuanxin Li, Yuejie Chi, Huishuai Zhang, Yingbin Liang
    Information and Inference: A Journal of the IMA, vol. 9, no. 2, pp. 289-325, 2020
  5. Provable nonconvex phase retrieval with outliers: A median approach
    Huishuai Zhang, Yuejie Chi, Yingbin Liang
    IEEE Transactions on Information Theory, 2018
  6. Reshaped Wirtinger flow and its incremental method for solving quadratic system of equations
    Huishuai Zhang, Yi Zhou, Yingbin Liang, Yuejie Chi
    Journal of Machine Learning Research, 2017
  7. Multi-key generation over a cellular model with a helper
    Huishuai Zhang, Yingbin Liang, Lifeng Lai, Shlomo Shamai
    IEEE Transactions on Information Theory, 2017
  8. The capacity region of the source-type model for secret key and private key generation
    Huishuai Zhang, Lifeng Lai, Yingbin Liang, Hua Wang
    IEEE Transaction on Information Theory, 60(10):6389-6398, October 2014

Services

I co-organized the workshop on Machine Learning Theory and Foundations with Lily Sun, Prof. Jingzhao Zhang, Prof. Pengkun Yang from Tsinghua University, and Greg Yang.

Conference Reviewers

Journal Reviewers


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