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Huishuai Zhang
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2020 – today
- 2024
- [j9]Da Yu, Sivakanth Gopi, Janardhan Kulkarni, Zinan Lin, Saurabh Naik, Tomasz Lukasz Religa, Jian Yin, Huishuai Zhang:
Selective Pre-training for Private Fine-tuning. Trans. Mach. Learn. Res. 2024 (2024) - [c39]Zhuocheng Gong, Ang Lv, Jian Guan, Wei Wu, Huishuai Zhang, Minlie Huang, Dongyan Zhao, Rui Yan:
Mixture-of-Modules: Reinventing Transformers as Dynamic Assemblies of Modules. EMNLP 2024: 20924-20938 - [c38]Chulin Xie, Zinan Lin, Arturs Backurs, Sivakanth Gopi, Da Yu, Huseyin A. Inan, Harsha Nori, Haotian Jiang, Huishuai Zhang, Yin Tat Lee, Bo Li, Sergey Yekhanin:
Differentially Private Synthetic Data via Foundation Model APIs 2: Text. ICML 2024 - [c37]Bohan Wang
, Yushun Zhang
Provable Adaptivity of Adam under Non-uniform Smoothness. KDD 2024: 2960-2969 - [i54]Chulin Xie, Zinan Lin, Arturs Backurs, Sivakanth Gopi, Da Yu, Huseyin A. Inan, Harsha Nori, Haotian Jiang, Huishuai Zhang, Yin Tat Lee, Bo Li, Sergey Yekhanin:
Differentially Private Synthetic Data via Foundation Model APIs 2: Text. CoRR abs/2403.01749 (2024) - [i53]Bohan Wang, Huishuai Zhang, Qi Meng, Ruoyu Sun, Zhi-Ming Ma, Wei Chen:
On the Convergence of Adam under Non-uniform Smoothness: Separability from SGDM and Beyond. CoRR abs/2403.15146 (2024) - [i52]Chao Zhou, Huishuai Zhang, Jiang Bian, Weiming Zhang, Nenghai Yu:
\copyright Plug-in Authorization for Human Content Copyright Protection in Text-to-Image Model. CoRR abs/2404.11962 (2024) - [i51]Xin Cheng, Xun Wang, Xingxing Zhang, Tao Ge, Si-Qing Chen, Furu Wei, Huishuai Zhang, Dongyan Zhao:
xRAG: Extreme Context Compression for Retrieval-augmented Generation with One Token. CoRR abs/2405.13792 (2024) - [i50]Minseon Kim, Hyomin Lee, Boqing Gong, Huishuai Zhang, Sung Ju Hwang:
Automatic Jailbreaking of the Text-to-Image Generative AI Systems. CoRR abs/2405.16567 (2024) - [i49]Yiduo Guo, Jie Fu, Huishuai Zhang, Dongyan Zhao, Yikang Shen:
Efficient Continual Pre-training by Mitigating the Stability Gap. CoRR abs/2406.14833 (2024) - [i48]Zhuocheng Gong, Ang Lv, Jian Guan, Junxi Yan, Wei Wu, Huishuai Zhang, Minlie Huang, Dongyan Zhao, Rui Yan:
Mixture-of-Modules: Reinventing Transformers as Dynamic Assemblies of Modules. CoRR abs/2407.06677 (2024) - [i47]Haowei Du, Huishuai Zhang, Dongyan Zhao:
Evidence-Enhanced Triplet Generation Framework for Hallucination Alleviation in Generative Question Answering. CoRR abs/2408.15037 (2024) - [i46]Danlong Yuan, Jiahao Liu, Bei Li, Huishuai Zhang, Jingang Wang, Xunliang Cai, Dongyan Zhao:
ReMamba: Equip Mamba with Effective Long-Sequence Modeling. CoRR abs/2408.15496 (2024) - [i45]Yueqian Wang, Jianxin Liang, Yuxuan Wang, Huishuai Zhang, Dongyan Zhao:
Understanding Multimodal Hallucination with Parameter-Free Representation Alignment. CoRR abs/2409.01151 (2024) - 2023
- [j8]Da Yu, Gautam Kamath, Janardhan Kulkarni, Tie-Yan Liu, Jian Yin, Huishuai Zhang:
Individual Privacy Accounting for Differentially Private Stochastic Gradient Descent. Trans. Mach. Learn. Res. 2023 (2023) - [c36]Junyao Gao
Similarity Distribution Based Membership Inference Attack on Person Re-identification. AAAI 2023: 14820-14828 - [c35]Huishuai Zhang, Da Yu, Yiping Lu, Di He:
Adversarial Noises Are Linearly Separable for (Nearly) Random Neural Networks. AISTATS 2023: 2792-2804 - [c34]Bohan Wang, Huishuai Zhang, Zhiming Ma, Wei Chen:
Convergence of AdaGrad for Non-convex Objectives: Simple Proofs and Relaxed Assumptions. COLT 2023: 161-190 - [c33]Hangting Ye, Zhining Liu, Xinyi Shen, Wei Cao, Shun Zheng, Xiaofan Gui, Huishuai Zhang, Yi Chang, Jiang Bian:
UADB: Unsupervised Anomaly Detection Booster. ICDE 2023: 2593-2606 - [c32]Jiyan He, Xuechen Li, Da Yu, Huishuai Zhang, Janardhan Kulkarni, Yin Tat Lee, Arturs Backurs, Nenghai Yu, Jiang Bian:
Exploring the Limits of Differentially Private Deep Learning with Group-wise Clipping. ICLR 2023 - [c31]Quanlin Wu, Hang Ye, Yuntian Gu, Huishuai Zhang, Liwei Wang, Di He:
Denoising Masked Autoencoders Help Robust Classification. ICLR 2023 - [c30]Kun Song, Huimin Ma, Bochao Zou, Huishuai Zhang, Weiran Huang:
FD-Align: Feature Discrimination Alignment for Fine-tuning Pre-Trained Models in Few-Shot Learning. NeurIPS 2023 - [c29]Puheng Li, Zhong Li, Huishuai Zhang, Jiang Bian:
On the Generalization Properties of Diffusion Models. NeurIPS 2023 - [c28]Bohan Wang, Jingwen Fu, Huishuai Zhang, Nanning Zheng, Wei Chen:
Closing the gap between the upper bound and lower bound of Adam's iteration complexity. NeurIPS 2023 - [c27]Kaipeng Zheng, Huishuai Zhang, Weiran Huang:
DiffKendall: A Novel Approach for Few-Shot Learning with Differentiable Kendall's Rank Correlation. NeurIPS 2023 - [i44]Shufang Xie, Huishuai Zhang, Junliang Guo, Xu Tan, Jiang Bian, Hany Hassan Awadalla, Arul Menezes, Tao Qin, Rui Yan:
ResiDual: Transformer with Dual Residual Connections. CoRR abs/2304.14802 (2023) - [i43]Da Yu, Sivakanth Gopi, Janardhan Kulkarni, Zinan Lin, Saurabh Naik, Tomasz Lukasz Religa, Jian Yin, Huishuai Zhang:
Selective Pre-training for Private Fine-tuning. CoRR abs/2305.13865 (2023) - [i42]Bohan Wang, Huishuai Zhang, Zhi-Ming Ma, Wei Chen:
Convergence of AdaGrad for Non-convex Objectives: Simple Proofs and Relaxed Assumptions. CoRR abs/2305.18471 (2023) - [i41]Hangting Ye, Zhining Liu, Xinyi Shen, Wei Cao, Shun Zheng, Xiaofan Gui, Huishuai Zhang, Yi Chang, Jiang Bian:
UADB: Unsupervised Anomaly Detection Booster. CoRR abs/2306.01997 (2023) - [i40]Jingwen Fu, Bohan Wang, Huishuai Zhang, Zhizheng Zhang, Wei Chen, Nanning Zheng:
When and Why Momentum Accelerates SGD: An Empirical Study. CoRR abs/2306.09000 (2023) - [i39]Zihao Jiang, Yunkai Dang, Dong Pang, Huishuai Zhang, Weiran Huang:
FILM: How can Few-Shot Image Classification Benefit from Pre-Trained Language Models? CoRR abs/2307.04114 (2023) - [i38]Kaipeng Zheng, Huishuai Zhang, Weiran Huang:
DiffKendall: A Novel Approach for Few-Shot Learning with Differentiable Kendall's Rank Correlation. CoRR abs/2307.15317 (2023) - [i37]Kun Song, Huimin Ma, Bochao Zou, Huishuai Zhang, Weiran Huang:
FD-Align: Feature Discrimination Alignment for Fine-tuning Pre-Trained Models in Few-Shot Learning. CoRR abs/2310.15105 (2023) - [i36]Bohan Wang, Jingwen Fu, Huishuai Zhang, Nanning Zheng, Wei Chen:
Closing the Gap Between the Upper Bound and the Lower Bound of Adam's Iteration Complexity. CoRR abs/2310.17998 (2023) - [i35]Puheng Li, Zhong Li, Huishuai Zhang, Jiang Bian:
On the Generalization Properties of Diffusion Models. CoRR abs/2311.01797 (2023) - [i34]Prin Phunyaphibarn, Junghyun Lee, Bohan Wang, Huishuai Zhang, Chulhee Yun:
Large Catapults in Momentum Gradient Descent with Warmup: An Empirical Study. CoRR abs/2311.15051 (2023) - [i33]Kai Qiu, Huishuai Zhang, Zhirong Wu, Stephen Lin:
Exploring Transferability for Randomized Smoothing. CoRR abs/2312.09020 (2023) - 2022
- [j7]Yi Zhou
Understanding generalization error of SGD in nonconvex optimization. Mach. Learn. 111(1): 345-375 (2022) - [j6]Huishuai Zhang
Stabilize deep ResNet with a sharp scaling factor τ. Mach. Learn. 111(9): 3359-3392 (2022) - [c26]Tianyu Pang
Two Coupled Rejection Metrics Can Tell Adversarial Examples Apart. CVPR 2022: 15202-15212 - [c25]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:
Differentially Private Fine-tuning of Language Models. ICLR 2022 - [c24]Zeke Xie, Xinrui Wang, Huishuai Zhang, Issei Sato, Masashi Sugiyama:
Adaptive Inertia: Disentangling the Effects of Adaptive Learning Rate and Momentum. ICML 2022: 24430-24459 - [c23]Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu:
Availability Attacks Create Shortcuts. KDD 2022: 2367-2376 - [c22]Bohan Wang, Qi Meng, Huishuai Zhang, Ruoyu Sun, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu:
Does Momentum Change the Implicit Regularization on Separable Data? NeurIPS 2022 - [i32]Jingwei Yi, Fangzhao Wu, Huishuai Zhang, Bin Zhu, Tao Qi, Guangzhong Sun, Xing Xie:
Robust Quantity-Aware Aggregation for Federated Learning. CoRR abs/2205.10848 (2022) - [i31]Da Yu, Gautam Kamath
Per-Instance Privacy Accounting for Differentially Private Stochastic Gradient Descent. CoRR abs/2206.02617 (2022) - [i30]Huishuai Zhang, Da Yu, Yiping Lu, Di He:
Adversarial Noises Are Linearly Separable for (Nearly) Random Neural Networks. CoRR abs/2206.04316 (2022) - [i29]Xiaodong Yang, Huishuai Zhang, Wei Chen, Tie-Yan Liu:
Normalized/Clipped SGD with Perturbation for Differentially Private Non-Convex Optimization. CoRR abs/2206.13033 (2022) - [i28]Bohan Wang, Yushun Zhang, Huishuai Zhang, Qi Meng, Zhi-Ming Ma, Tie-Yan Liu, Wei Chen:
Provable Adaptivity in Adam. CoRR abs/2208.09900 (2022) - [i27]Quanlin Wu, Hang Ye, Yuntian Gu, Huishuai Zhang, Liwei Wang, Di He:
Denoising Masked AutoEncoders are Certifiable Robust Vision Learners. CoRR abs/2210.06983 (2022) - [i26]Junyao Gao, Xinyang Jiang, Huishuai Zhang, Yifan Yang, Shuguang Dou
Similarity Distribution based Membership Inference Attack on Person Re-identification. CoRR abs/2211.15918 (2022) - [i25]Jiyan He, Xuechen Li, Da Yu, Huishuai Zhang, Janardhan Kulkarni, Yin Tat Lee, Arturs Backurs, Nenghai Yu, Jiang Bian:
Exploring the Limits of Differentially Private Deep Learning with Group-wise Clipping. CoRR abs/2212.01539 (2022) - 2021
- [c21]Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu:
How Does Data Augmentation Affect Privacy in Machine Learning? AAAI 2021: 10746-10753 - [c20]Da Yu, Huishuai Zhang, Wei Chen, Tie-Yan Liu:
Do not Let Privacy Overbill Utility: Gradient Embedding Perturbation for Private Learning. ICLR 2021 - [c19]Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu:
Large Scale Private Learning via Low-rank Reparametrization. ICML 2021: 12208-12218 - [c18]Bohan Wang, Huishuai Zhang, Jieyu Zhang, Qi Meng, Wei Chen, Tie-Yan Liu:
Optimizing Information-theoretical Generalization Bound via Anisotropic Noise of SGLD. NeurIPS 2021: 26080-26090 - [i24]Mingyang Yi, Huishuai Zhang, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu:
BN-invariant sharpness regularizes the training model to better generalization. CoRR abs/2101.02944 (2021) - [i23]Da Yu, Huishuai Zhang, Wei Chen, Tie-Yan Liu:
Do Not Let Privacy Overbill Utility: Gradient Embedding Perturbation for Private Learning. CoRR abs/2102.12677 (2021) - [i22]Tianyu Pang, Huishuai Zhang, Di He, Yinpeng Dong, Hang Su, Wei Chen, Jun Zhu, Tie-Yan Liu:
Adversarial Training with Rectified Rejection. CoRR abs/2105.14785 (2021) - [i21]Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu:
Large Scale Private Learning via Low-rank Reparametrization. CoRR abs/2106.09352 (2021) - [i20]Yichi Zhou, Shihong Song, Huishuai Zhang, Jun Zhu, Wei Chen, Tie-Yan Liu:
Regularized OFU: an Efficient UCB Estimator forNon-linear Contextual Bandit. CoRR abs/2106.15128 (2021) - [i19]Bohan Wang, Qi Meng, Huishuai Zhang, Ruoyu Sun, Wei Chen, Zhi-Ming Ma:
Momentum Doesn't Change the Implicit Bias. CoRR abs/2110.03891 (2021) - [i18]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:
Differentially Private Fine-tuning of Language Models. CoRR abs/2110.06500 (2021) - [i17]Bohan Wang, Huishuai Zhang, Jieyu Zhang, Qi Meng, Wei Chen, Tie-Yan Liu:
Optimizing Information-theoretical Generalization Bounds via Anisotropic Noise in SGLD. CoRR abs/2110.13750 (2021) - [i16]Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu:
Indiscriminate Poisoning Attacks Are Shortcuts. CoRR abs/2111.00898 (2021) - 2020
- [j5]Shicong Cen, Huishuai Zhang, Yuejie Chi
Convergence of Distributed Stochastic Variance Reduced Methods Without Sampling Extra Data. IEEE Trans. Signal Process. 68: 3976-3989 (2020) - [c17]Ruibin Xiong, Yunchang Yang, Di He, Kai Zheng, Shuxin Zheng, Chen Xing, Huishuai Zhang, Yanyan Lan, Liwei Wang, Tie-Yan Liu:
On Layer Normalization in the Transformer Architecture. ICML 2020: 10524-10533 - [c16]Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu:
Gradient Perturbation is Underrated for Differentially Private Convex Optimization. IJCAI 2020: 3117-3123 - [i15]Ruibin Xiong, Yunchang Yang, Di He, Kai Zheng, Shuxin Zheng
On Layer Normalization in the Transformer Architecture. CoRR abs/2002.04745 (2020) - [i14]Zeke Xie, Xinrui Wang, Huishuai Zhang, Issei Sato, Masashi Sugiyama:
Adai: Separating the Effects of Adaptive Learning Rate and Momentum Inertia. CoRR abs/2006.15815 (2020) - [i13]Da Yu, Huishuai Zhang, Wei Chen, Jian Yin, Tie-Yan Liu:
Membership Inference with Privately Augmented Data Endorses the Benign while Suppresses the Adversary. CoRR abs/2007.10567 (2020) - [i12]Jerry Li, Aaron Sidford, Kevin Tian, Huishuai Zhang:
Well-Conditioned Methods for Ill-Conditioned Systems: Linear Regression with Semi-Random Noise. CoRR abs/2008.01722 (2020)
2010 – 2019
- 2019
- [c15]Shuxin Zheng, Qi Meng, Huishuai Zhang, Wei Chen, Nenghai Yu, Tie-Yan Liu:
Capacity Control of ReLU Neural Networks by Basis-Path Norm. AAAI 2019: 5925-5932 - [c14]Qi Meng, Shuxin Zheng, Huishuai Zhang, Wei Chen, Qiwei Ye, Zhi-Ming Ma, Nenghai Yu, Tie-Yan Liu:
G-SGD: Optimizing ReLU Neural Networks in its Positively Scale-Invariant Space. ICLR (Poster) 2019 - [c13]Yi Zhou, Junjie Yang, Huishuai Zhang, Yingbin Liang, Vahid Tarokh:
SGD Converges to Global Minimum in Deep Learning via Star-convex Path. ICLR (Poster) 2019 - [c12]Mingyang Yi, Huishuai Zhang, Wei Chen, Zhi-Ming Ma, Tie-Yan Liu:
BN-invariant Sharpness Regularizes the Training Model to Better Generalization. IJCAI 2019: 4164-4170 - [i11]Yi Zhou, Junjie Yang, Huishuai Zhang, Yingbin Liang, Vahid Tarokh:
SGD Converges to Global Minimum in Deep Learning via Star-convex Path. CoRR abs/1901.00451 (2019) - [i10]Huishuai Zhang, Da Yu, Wei Chen, Tie-Yan Liu:
Training Over-parameterized Deep ResNet Is almost as Easy as Training a Two-layer Network. CoRR abs/1903.07120 (2019) - [i9]Shicong Cen, Huishuai Zhang, Yuejie Chi, Wei Chen, Tie-Yan Liu:
Convergence of Distributed Stochastic Variance Reduced Methods without Sampling Extra Data. CoRR abs/1905.12648 (2019) - [i8]Da Yu, Huishuai Zhang, Wei Chen, Tie-Yan Liu, Jian Yin:
Gradient Perturbation is Underrated for Differentially Private Convex Optimization. CoRR abs/1911.11363 (2019) - 2018
- [j4]Huishuai Zhang
Median-Truncated Nonconvex Approach for Phase Retrieval With Outliers. IEEE Trans. Inf. Theory 64(11): 7287-7310 (2018) - [c11]Huishuai Zhang, Wei Chen, Tie-Yan Liu:
On the Local Hessian in Back-propagation. NeurIPS 2018: 6521-6531 - [i7]Yi Zhou, Yingbin Liang, Huishuai Zhang:
Generalization Error Bounds with Probabilistic Guarantee for SGD in Nonconvex Optimization. CoRR abs/1802.06903 (2018) - [i6]Huishuai Zhang, Wei Chen, Tie-Yan Liu:
Train Feedfoward Neural Network with Layer-wise Adaptive Rate via Approximating Back-matching Propagation. CoRR abs/1802.09750 (2018) - [i5]Shuxin Zheng
Capacity Control of ReLU Neural Networks by Basis-path Norm. CoRR abs/1809.07122 (2018) - 2017
- [j3]Huishuai Zhang, Yingbin Liang, Yuejie Chi:
A Nonconvex Approach for Phase Retrieval: Reshaped Wirtinger Flow and Incremental Algorithms. J. Mach. Learn. Res. 18: 141:1-141:35 (2017) - [j2]Huishuai Zhang
Multi-Key Generation Over a Cellular Model With a Helper. IEEE Trans. Inf. Theory 63(6): 3804-3822 (2017) - [i4]Yuanxin Li, Yuejie Chi, Huishuai Zhang, Yingbin Liang:
Nonconvex Low-Rank Matrix Recovery with Arbitrary Outliers via Median-Truncated Gradient Descent. CoRR abs/1709.08114 (2017) - [i3]Huishuai Zhang, Caiming Xiong, James Bradbury, Richard Socher:
Block-diagonal Hessian-free Optimization for Training Neural Networks. CoRR abs/1712.07296 (2017) - 2016
- [c10]Yi Zhou, Huishuai Zhang, Yingbin Liang:
On Compressive orthonormal Sensing. Allerton 2016: 299-305 - [c9]Yi Zhou, Huishuai Zhang, Yingbin Liang:
Geometrical properties and accelerated gradient solvers of non-convex phase retrieval. Allerton 2016: 331-335 - [c8]Huishuai Zhang, Yuejie Chi, Yingbin Liang:
Provable Non-convex Phase Retrieval with Outliers: Median TruncatedWirtinger Flow. ICML 2016: 1022-1031 - [c7]Huishuai Zhang, Yingbin Liang:
Reshaped Wirtinger Flow for Solving Quadratic System of Equations. NIPS 2016: 2622-2630 - [i2]Huishuai Zhang, Yingbin Liang:
Reshaped Wirtinger Flow for Solving Quadratic Systems of Equations. CoRR abs/1605.07719 (2016) - 2015
- [c6]Huishuai Zhang, Yingbin Liang, Lifeng Lai:
Secret key capacity: Talk or keep silent? ISIT 2015: 291-295 - [c5]Huishuai Zhang, Yingbin Liang, Lifeng Lai, Shlomo Shamai
Two-key generation for a cellular model with a helper. ISIT 2015: 715-719 - [c4]Huishuai Zhang, Yi Zhou, Yingbin Liang:
Analysis of Robust PCA via Local Incoherence. NIPS 2015: 1819-1827 - 2014
- [j1]Huishuai Zhang, Lifeng Lai, Yingbin Liang, Hua Wang:
The Capacity Region of the Source-Type Model for Secret Key and Private Key Generation. IEEE Trans. Inf. Theory 60(10): 6389-6398 (2014) - [c3]Huishuai Zhang, Yingbin Liang, Lifeng Lai:
Helper-assisted asymmetric two key generation. ACSSC 2014: 65-69 - [c2]Huishuai Zhang, Lifeng Lai, Yingbin Liang, Hua Wang:
Secret key-private key generation over three terminals: Capacity region. ISIT 2014: 1141-1145 - [c1]Huishuai Zhang, Yingbin Liang, Lifeng Lai:
Key capacity region for a cellular source model. ITW 2014: 321-325 - [i1]Huishuai Zhang, Lifeng Lai, Yingbin Liang, Hua Wang:
The Capacity Region of the Source-Type Model for Secret Key and Private Key Generation. CoRR abs/1404.6471 (2014)
Coauthor Index
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