Helper-assisted asymmetric two key generation. - Huishuai Zhang; Yingbin Liang; Lifeng Lai (ACSSC, 2014)

Secret key-private key generation over three terminals: Capacity region. - Huishuai Zhang; Lifeng Lai; Yingbin Liang; Hua Wang (ISIT, 2014)

Key capacity region for a cellular source model. - Huishuai Zhang; Yingbin Liang; Lifeng Lai (ITW, 2014)

The Capacity Region of the Source-Type Model for Secret Key and Private Key Generation. - Huishuai Zhang; Lifeng Lai; Yingbin Liang; Hua Wang (IEEE Trans. Inf. Theory, 2014)

Secret key capacity: Talk or keep silent? - Huishuai Zhang; Yingbin Liang; Lifeng Lai (ISIT, 2015)

Two-key generation for a cellular model with a helper. - Huishuai Zhang; Yingbin Liang; Lifeng Lai; Shlomo Shamai (ISIT, 2015)

Analysis of Robust PCA via Local Incoherence. - Huishuai Zhang; Yi Zhou 017; Yingbin Liang (NIPS, 2015)

On Compressive orthonormal Sensing. - Yi Zhou 017; Huishuai Zhang; Yingbin Liang (Allerton, 2016)

Geometrical properties and accelerated gradient solvers of non-convex phase retrieval. - Yi Zhou 017; Huishuai Zhang; Yingbin Liang (Allerton, 2016)

Provable Non-convex Phase Retrieval with Outliers: Median TruncatedWirtinger Flow. - Huishuai Zhang; Yuejie Chi; Yingbin Liang (ICML, 2016)

Reshaped Wirtinger Flow for Solving Quadratic System of Equations. - Huishuai Zhang; Yingbin Liang (NIPS, 2016)

Reshaped Wirtinger Flow for Solving Quadratic Systems of Equations. - Huishuai Zhang; Yingbin Liang (CoRR, 2016)

Nonconvex Low-Rank Matrix Recovery with Arbitrary Outliers via Median-Truncated Gradient Descent. - Yuanxin Li 003; Yuejie Chi; Huishuai Zhang; Yingbin Liang (CoRR, 2017)

Block-diagonal Hessian-free Optimization for Training Neural Networks. - Huishuai Zhang; Caiming Xiong; James Bradbury 002; Richard Socher (CoRR, 2017)

A Nonconvex Approach for Phase Retrieval: Reshaped Wirtinger Flow and Incremental Algorithms. - Huishuai Zhang; Yingbin Liang; Yuejie Chi (J. Mach. Learn. Res., 2017)

Multi-Key Generation Over a Cellular Model With a Helper. - Huishuai Zhang; Yingbin Liang; Lifeng Lai; Shlomo Shamai Shitz (IEEE Trans. Inf. Theory, 2017)

On the Local Hessian in Back-propagation. - Huishuai Zhang; Wei Chen 034; Tie-Yan Liu (NeurIPS, 2018)

Generalization Error Bounds with Probabilistic Guarantee for SGD in Nonconvex Optimization. - Yi Zhou 017; Yingbin Liang; Huishuai Zhang (CoRR, 2018)

Train Feedfoward Neural Network with Layer-wise Adaptive Rate via Approximating Back-matching Propagation. - Huishuai Zhang; Wei Chen 034; Tie-Yan Liu (CoRR, 2018)

Median-Truncated Nonconvex Approach for Phase Retrieval With Outliers. - Huishuai Zhang; Yuejie Chi; Yingbin Liang (IEEE Trans. Inf. Theory, 2018)

Capacity Control of ReLU Neural Networks by Basis-Path Norm. - Shuxin Zheng; Qi Meng; Huishuai Zhang; Wei Chen 034; Nenghai Yu; Tie-Yan Liu (AAAI, 2019)

G-SGD: Optimizing ReLU Neural Networks in its Positively Scale-Invariant Space. - Qi Meng; Shuxin Zheng; Huishuai Zhang; Wei Chen 034; Qiwei Ye; Zhi-Ming Ma; Nenghai Yu; Tie-Yan Liu (ICLR (Poster), 2019)

SGD Converges to Global Minimum in Deep Learning via Star-convex Path. - Yi Zhou 017; Junjie Yang; Huishuai Zhang; Yingbin Liang; Vahid Tarokh (ICLR (Poster), 2019)

BN-invariant Sharpness Regularizes the Training Model to Better Generalization. - Mingyang Yi; Huishuai Zhang; Wei Chen 034; Zhi-Ming Ma; Tie-Yan Liu (IJCAI, 2019)

Training Over-parameterized Deep ResNet Is almost as Easy as Training a Two-layer Network. - Huishuai Zhang; Da Yu; Wei Chen 034; Tie-Yan Liu (CoRR, 2019)

On Layer Normalization in the Transformer Architecture. - Ruibin Xiong; Yunchang Yang; Di He 001; Kai Zheng 007; Shuxin Zheng; Chen Xing; Huishuai Zhang; Yanyan Lan; Liwei Wang 001; Tie-Yan Liu (ICML, 2020)

Gradient Perturbation is Underrated for Differentially Private Convex Optimization. - Da Yu; Huishuai Zhang; Wei Chen 034; Jian Yin 001; Tie-Yan Liu (IJCAI, 2020)

Adai: Separating the Effects of Adaptive Learning Rate and Momentum Inertia. - Zeke Xie; Xinrui Wang; Huishuai Zhang; Issei Sato; Masashi Sugiyama (CoRR, 2020)

Membership Inference with Privately Augmented Data Endorses the Benign while Suppresses the Adversary. - Da Yu; Huishuai Zhang; Wei Chen 034; Jian Yin 001; Tie-Yan Liu (CoRR, 2020)

Well-Conditioned Methods for Ill-Conditioned Systems: Linear Regression with Semi-Random Noise. - Jerry Li 001; Aaron Sidford; Kevin Tian; Huishuai Zhang (CoRR, 2020)

Convergence of Distributed Stochastic Variance Reduced Methods Without Sampling Extra Data. - Shicong Cen; Huishuai Zhang; Yuejie Chi; Wei Chen 034; Tie-Yan Liu (IEEE Trans. Signal Process., 2020)

How Does Data Augmentation Affect Privacy in Machine Learning? - Da Yu; Huishuai Zhang; Wei Chen 034; Jian Yin 001; Tie-Yan Liu (AAAI, 2021)

Do not Let Privacy Overbill Utility: Gradient Embedding Perturbation for Private Learning. - Da Yu; Huishuai Zhang; Wei Chen 034; Tie-Yan Liu (ICLR, 2021)

Large Scale Private Learning via Low-rank Reparametrization. - Da Yu; Huishuai Zhang; Wei Chen 034; Jian Yin 001; Tie-Yan Liu (ICML, 2021)

Optimizing Information-theoretical Generalization Bound via Anisotropic Noise of SGLD. - Bohan Wang; Huishuai Zhang; Jieyu Zhang; Qi Meng; Wei Chen 034; Tie-Yan Liu (NeurIPS, 2021)

Adversarial Training with Rectified Rejection. - Tianyu Pang; Huishuai Zhang; Di He 001; Yinpeng Dong; Hang Su 006; Wei Chen 034; Jun Zhu 001; Tie-Yan Liu (CoRR, 2021)

Regularized OFU: an Efficient UCB Estimator forNon-linear Contextual Bandit. - Yichi Zhou; Shihong Song; Huishuai Zhang; Jun Zhu 001; Wei Chen 034; Tie-Yan Liu (CoRR, 2021)

Momentum Doesn't Change the Implicit Bias. - Bohan Wang; Qi Meng; Huishuai Zhang; Ruoyu Sun 001; Wei Chen 034; Zhi-Ming Ma (CoRR, 2021)

Optimizing Information-theoretical Generalization Bounds via Anisotropic Noise in SGLD. - Bohan Wang; Huishuai Zhang; Jieyu Zhang; Qi Meng; Wei Chen 034; Tie-Yan Liu (CoRR, 2021)

Indiscriminate Poisoning Attacks Are Shortcuts. - Da Yu; Huishuai Zhang; Wei Chen 034; Jian Yin 001; Tie-Yan Liu (CoRR, 2021)

Two Coupled Rejection Metrics Can Tell Adversarial Examples Apart. - Tianyu Pang; Huishuai Zhang; Di He 001; Yinpeng Dong; Hang Su 006; Wei Chen 034; Jun Zhu 001; Tie-Yan Liu (CVPR, 2022)

Adaptive Inertia: Disentangling the Effects of Adaptive Learning Rate and Momentum. - Zeke Xie; Xinrui Wang; Huishuai Zhang; Issei Sato; Masashi Sugiyama (ICML, 2022)

Availability Attacks Create Shortcuts. - Da Yu; Huishuai Zhang; Wei Chen 034; Jian Yin 001; Tie-Yan Liu (KDD, 2022)

Does Momentum Change the Implicit Regularization on Separable Data? - Bohan Wang; Qi Meng; Huishuai Zhang; Ruoyu Sun 001; Wei Chen 034; Zhi-Ming Ma; Tie-Yan Liu (NeurIPS, 2022)

Robust Quantity-Aware Aggregation for Federated Learning. - Jingwei Yi; Fangzhao Wu; Huishuai Zhang; Bin Zhu 008; Tao Qi; Guangzhong Sun; Xing Xie 001 (CoRR, 2022)

Per-Instance Privacy Accounting for Differentially Private Stochastic Gradient Descent. - Da Yu; Gautam Kamath 001; Janardhan Kulkarni; Tie-Yan Liu; Jian Yin 001; Huishuai Zhang (CoRR, 2022)

Normalized/Clipped SGD with Perturbation for Differentially Private Non-Convex Optimization. - Xiaodong Yang; Huishuai Zhang; Wei Chen 034; Tie-Yan Liu (CoRR, 2022)

Provable Adaptivity in Adam. - Bohan Wang; Yushun Zhang; Huishuai Zhang; Qi Meng; Zhi-Ming Ma; Tie-Yan Liu; Wei Chen 034 (CoRR, 2022)

Denoising Masked AutoEncoders are Certifiable Robust Vision Learners. - Quanlin Wu; Hang Ye 002; Yuntian Gu; Huishuai Zhang; Liwei Wang 001; Di He 001 (CoRR, 2022)

Stabilize deep ResNet with a sharp scaling factor τ. - Huishuai Zhang; Da Yu; Mingyang Yi; Wei Chen 034; Tie-Yan Liu (Mach. Learn., 2022)

Understanding generalization error of SGD in nonconvex optimization. - Yi Zhou 017; Yingbin Liang; Huishuai Zhang (Mach. Learn., 2022)

Similarity Distribution Based Membership Inference Attack on Person Re-identification. - Junyao Gao 002; Xinyang Jiang; Huishuai Zhang; Yifan Yang 004; Shuguang Dou; Dongsheng Li 002; Duoqian Miao 001; Cheng Deng; Cairong Zhao (AAAI, 2023)

Adversarial Noises Are Linearly Separable for (Nearly) Random Neural Networks. - Huishuai Zhang; Da Yu; Yiping Lu 001; Di He 001 (AISTATS, 2023)

Convergence of AdaGrad for Non-convex Objectives: Simple Proofs and Relaxed Assumptions. - Bohan Wang; Huishuai Zhang; Zhiming Ma; Wei Chen 034 (COLT, 2023)

UADB: Unsupervised Anomaly Detection Booster. - Hangting Ye; Zhining Liu 002; Xinyi Shen; Wei Cao 007; Shun Zheng 001; Xiaofan Gui; Huishuai Zhang; Yi Chang 001; Jiang Bian 002 (ICDE, 2023)

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 002 (ICLR, 2023)

Denoising Masked Autoencoders Help Robust Classification. - Quanlin Wu; Hang Ye 002; Yuntian Gu; Huishuai Zhang; Liwei Wang 001; Di He 001 (ICLR, 2023)

FD-Align: Feature Discrimination Alignment for Fine-tuning Pre-Trained Models in Few-Shot Learning. - Kun Song 004; Huimin Ma 001; Bochao Zou; Huishuai Zhang; Weiran Huang 001 (NeurIPS, 2023)

On the Generalization Properties of Diffusion Models. - Puheng Li; Zhong Li 004; Huishuai Zhang; Jiang Bian 002 (NeurIPS, 2023)

Closing the gap between the upper bound and lower bound of Adam's iteration complexity. - Bohan Wang; Jingwen Fu; Huishuai Zhang; Nanning Zheng 001; Wei Chen 034 (NeurIPS, 2023)

DiffKendall: A Novel Approach for Few-Shot Learning with Differentiable Kendall's Rank Correlation. - Kaipeng Zheng; Huishuai Zhang; Weiran Huang 001 (NeurIPS, 2023)

ResiDual: Transformer with Dual Residual Connections. - Shufang Xie 003; Huishuai Zhang; Junliang Guo; Xu Tan 003; Jiang Bian 002; Hany Hassan Awadalla; Arul Menezes; Tao Qin 001; Rui Yan 001 (CoRR, 2023)

When and Why Momentum Accelerates SGD: An Empirical Study. - Jingwen Fu; Bohan Wang; Huishuai Zhang; Zhizheng Zhang 004; Wei Chen 034; Nanning Zheng 001 (CoRR, 2023)

FILM: How can Few-Shot Image Classification Benefit from Pre-Trained Language Models? - Zihao Jiang 005; Yunkai Dang; Dong Pang; Huishuai Zhang; Weiran Huang 001 (CoRR, 2023)

Large Catapults in Momentum Gradient Descent with Warmup: An Empirical Study. - Prin Phunyaphibarn; Junghyun Lee; Bohan Wang; Huishuai Zhang; Chulhee Yun (CoRR, 2023)

Exploring Transferability for Randomized Smoothing. - Kai Qiu; Huishuai Zhang; Zhirong Wu; Stephen Lin 001 (CoRR, 2023)

Individual Privacy Accounting for Differentially Private Stochastic Gradient Descent. - Da Yu; Gautam Kamath 001; Janardhan Kulkarni; Tie-Yan Liu; Jian Yin 001; Huishuai Zhang (Trans. Mach. Learn. Res., 2023)

Mixture-of-Modules: Reinventing Transformers as Dynamic Assemblies of Modules. - Zhuocheng Gong; Ang Lv; Jian Guan 002; Wei Wu 014; Huishuai Zhang; Minlie Huang; Dongyan Zhao 001; Rui Yan 001 (EMNLP, 2024)

Differentially Private Synthetic Data via Foundation Model APIs 2: Text. - Chulin Xie; Zinan Lin 001; Arturs Backurs; Sivakanth Gopi; Da Yu; Huseyin A. Inan; Harsha Nori; Haotian Jiang; Huishuai Zhang; Yin Tat Lee; Bo Li 026; Sergey Yekhanin (ICML, 2024)

Provable Adaptivity of Adam under Non-uniform Smoothness. - Bohan Wang; Yushun Zhang; Huishuai Zhang; Qi Meng; Ruoyu Sun 001; Zhi-Ming Ma; Tie-Yan Liu; Zhi-Quan Luo; Wei Chen 034 (KDD, 2024)

xRAG: Extreme Context Compression for Retrieval-augmented Generation with One Token. - Xin Cheng 002; Xun Wang 012; Xingxing Zhang 002; Tao Ge 001; Si-Qing Chen; Furu Wei; Huishuai Zhang; Dongyan Zhao 001 (NeurIPS, 2024)

On the Convergence of Adam under Non-uniform Smoothness: Separability from SGDM and Beyond. - Bohan Wang; Huishuai Zhang; Qi Meng; Ruoyu Sun 001; Zhi-Ming Ma; Wei Chen 034 (CoRR, 2024)

copyright Plug-in Authorization for Human Content Copyright Protection in Text-to-Image Model. - Chao Zhou; Huishuai Zhang; Jiang Bian 002; Weiming Zhang 001; Nenghai Yu (CoRR, 2024)

Automatic Jailbreaking of the Text-to-Image Generative AI Systems. - Minseon Kim; Hyomin Lee; Boqing Gong; Huishuai Zhang; Sung Ju Hwang (CoRR, 2024)

Efficient Continual Pre-training by Mitigating the Stability Gap. - Yiduo Guo; Jie Fu; Huishuai Zhang; Dongyan Zhao 001; Yikang Shen (CoRR, 2024)

Mixture-of-Modules: Reinventing Transformers as Dynamic Assemblies of Modules. - Zhuocheng Gong; Ang Lv; Jian Guan 002; Junxi Yan; Wei Wu 014; Huishuai Zhang; Minlie Huang; Dongyan Zhao 001; Rui Yan 001 (CoRR, 2024)

Evidence-Enhanced Triplet Generation Framework for Hallucination Alleviation in Generative Question Answering. - Haowei Du; Huishuai Zhang; Dongyan Zhao 001 (CoRR, 2024)

ReMamba: Equip Mamba with Effective Long-Sequence Modeling. - Danlong Yuan; Jiahao Liu; Bei Li; Huishuai Zhang; Jingang Wang; Xunliang Cai; Dongyan Zhao 001 (CoRR, 2024)

Understanding Multimodal Hallucination with Parameter-Free Representation Alignment. - Yueqian Wang; Jianxin Liang; Yuxuan Wang 004; Huishuai Zhang; Dongyan Zhao 001 (CoRR, 2024)

AIDBench: A benchmark for evaluating the authorship identification capability of large language models. - Zichen Wen; Dadi Guo; Huishuai Zhang (CoRR, 2024)

VideoLLM Knows When to Speak: Enhancing Time-Sensitive Video Comprehension with Video-Text Duet Interaction Format. - Yueqian Wang; Xiaojun Meng; Yuxuan Wang 004; Jianxin Liang; Jiansheng Wei; Huishuai Zhang; Dongyan Zhao 001 (CoRR, 2024)

Differentially Private Fine-tuning of Language Models. - Da Yu; Saurabh Naik; Arturs Backurs; Sivakanth Gopi; Huseyin A. Inan; Gautam Kamath 001; Janardhan Kulkarni; Yin Tat Lee; Andre Manoel; Lukas Wutschitz; Sergey Yekhanin; Huishuai Zhang (J. Priv. Confidentiality, 2024)

Selective Pre-training for Private Fine-tuning. - Da Yu; Sivakanth Gopi; Janardhan Kulkarni; Zinan Lin 001; Saurabh Naik; Tomasz Lukasz Religa; Jian Yin 001; Huishuai Zhang (Trans. Mach. Learn. Res., 2024)

Efficient Domain Continual pretraining by Mitigating the Stability Gap. - Yiduo Guo; Jie Fu; Huishuai Zhang; Dongyan Zhao 001 (ACL (1), 2025)

ReasVQA: Advancing VideoQA with Imperfect Reasoning Process. - Jianxin Liang; Xiaojun Meng; Huishuai Zhang; Yueqian Wang; Jiansheng Wei; Dongyan Zhao 001 (NAACL (Long Papers), 2025)

©Plug-in Authorization for Human Copyright Protection in Text-to-Image Model. - Chao Zhou; Huishuai Zhang; Jiang Bian 002; Weiming Zhang 001; Nenghai Yu (Trans. Mach. Learn. Res., 2025)

Latent Preference Coding: Aligning Large Language Models via Discrete Latent Codes. - Zhuocheng Gong; Jian Guan 002; Wei Wu 014; Huishuai Zhang; Dongyan Zhao 001 (CoRR, 2025)

Understanding Nonlinear Implicit Bias via Region Counts in Input Space. - Jingwei Li; Jing Xu; Zifan Wang; Huishuai Zhang; Jingzhao Zhang (CoRR, 2025)

Efficient RL Training for Reasoning Models via Length-Aware Optimization. - Danlong Yuan; Tian Xie; Shaohan Huang; Zhuocheng Gong; Huishuai Zhang; Chong Luo; Furu Wei; Dongyan Zhao 001 (CoRR, 2025)

AdamS: Momentum Itself Can Be A Normalizer for LLM Pretraining and Post-training. - Huishuai Zhang; Bohan Wang; Luoxin Chen (CoRR, 2025)

Synthetic Data RL: Task Definition Is All You Need. - Yiduo Guo; Zhen Guo; Chuanwei Huang; Zi-Ang Wang; Zekai Zhang; Haofei Yu; Huishuai Zhang; Yikang Shen (CoRR, 2025)

Synthesize Privacy-Preserving High-Resolution Images via Private Textual Intermediaries. - Haoxiang Wang; Zinan Lin 001; Da Yu; Huishuai Zhang (CoRR, 2025)

ProactiveVideoQA: A Comprehensive Benchmark Evaluating Proactive Interactions in Video Large Language Models. - Yueqian Wang; Xiaojun Meng; Yifan Wang; Huishuai Zhang; Dongyan Zhao 001 (CoRR, 2025)

Solving Formal Math Problems by Decomposition and Iterative Reflection. - Yichi Zhou; Jianqiu Zhao; Yongxin Zhang; Bohan Wang; Siran Wang; Luoxin Chen; Jiahui Wang; Haowei Chen; Allan Jie; Xinbo Zhang; Haocheng Wang; Luong Quoc Trung; et al. (CoRR, 2025)