Huishuai Zhang

Orcid: 0000-0003-2711-7295

According to our database1, Huishuai Zhang authored at least 81 papers between 2014 and 2024.

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Bibliography

2024
Selective Pre-training for Private Fine-tuning.
Trans. Mach. Learn. Res., 2024

Differentially Private Fine-tuning of Language Models.
J. Priv. Confidentiality, 2024

Understanding Multimodal Hallucination with Parameter-Free Representation Alignment.
CoRR, 2024

ReMamba: Equip Mamba with Effective Long-Sequence Modeling.
CoRR, 2024

Evidence-Enhanced Triplet Generation Framework for Hallucination Alleviation in Generative Question Answering.
CoRR, 2024

Mixture-of-Modules: Reinventing Transformers as Dynamic Assemblies of Modules.
CoRR, 2024

Efficient Continual Pre-training by Mitigating the Stability Gap.
CoRR, 2024

Automatic Jailbreaking of the Text-to-Image Generative AI Systems.
CoRR, 2024

xRAG: Extreme Context Compression for Retrieval-augmented Generation with One Token.
CoRR, 2024

\copyright Plug-in Authorization for Human Content Copyright Protection in Text-to-Image Model.
CoRR, 2024

On the Convergence of Adam under Non-uniform Smoothness: Separability from SGDM and Beyond.
CoRR, 2024

Provable Adaptivity of Adam under Non-uniform Smoothness.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Differentially Private Synthetic Data via Foundation Model APIs 2: Text.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Mixture-of-Modules: Reinventing Transformers as Dynamic Assemblies of Modules.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

2023
Individual Privacy Accounting for Differentially Private Stochastic Gradient Descent.
Trans. Mach. Learn. Res., 2023

Exploring Transferability for Randomized Smoothing.
CoRR, 2023

Large Catapults in Momentum Gradient Descent with Warmup: An Empirical Study.
CoRR, 2023

FILM: How can Few-Shot Image Classification Benefit from Pre-Trained Language Models?
CoRR, 2023

When and Why Momentum Accelerates SGD: An Empirical Study.
CoRR, 2023

ResiDual: Transformer with Dual Residual Connections.
CoRR, 2023

DiffKendall: A Novel Approach for Few-Shot Learning with Differentiable Kendall's Rank Correlation.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Closing the gap between the upper bound and lower bound of Adam's iteration complexity.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

On the Generalization Properties of Diffusion Models.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

FD-Align: Feature Discrimination Alignment for Fine-tuning Pre-Trained Models in Few-Shot Learning.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Denoising Masked Autoencoders Help Robust Classification.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Exploring the Limits of Differentially Private Deep Learning with Group-wise Clipping.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

UADB: Unsupervised Anomaly Detection Booster.
Proceedings of the 39th IEEE International Conference on Data Engineering, 2023

Convergence of AdaGrad for Non-convex Objectives: Simple Proofs and Relaxed Assumptions.
Proceedings of the Thirty Sixth Annual Conference on Learning Theory, 2023

Adversarial Noises Are Linearly Separable for (Nearly) Random Neural Networks.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

Similarity Distribution Based Membership Inference Attack on Person Re-identification.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Understanding generalization error of SGD in nonconvex optimization.
Mach. Learn., 2022

Stabilize deep ResNet with a sharp scaling factor τ.
Mach. Learn., 2022

Denoising Masked AutoEncoders are Certifiable Robust Vision Learners.
CoRR, 2022

Provable Adaptivity in Adam.
CoRR, 2022

Normalized/Clipped SGD with Perturbation for Differentially Private Non-Convex Optimization.
CoRR, 2022

Per-Instance Privacy Accounting for Differentially Private Stochastic Gradient Descent.
CoRR, 2022

Robust Quantity-Aware Aggregation for Federated Learning.
CoRR, 2022

Does Momentum Change the Implicit Regularization on Separable Data?
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Availability Attacks Create Shortcuts.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Adaptive Inertia: Disentangling the Effects of Adaptive Learning Rate and Momentum.
Proceedings of the International Conference on Machine Learning, 2022

Two Coupled Rejection Metrics Can Tell Adversarial Examples Apart.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021
Indiscriminate Poisoning Attacks Are Shortcuts.
CoRR, 2021

Optimizing Information-theoretical Generalization Bounds via Anisotropic Noise in SGLD.
CoRR, 2021

Momentum Doesn't Change the Implicit Bias.
CoRR, 2021

Regularized OFU: an Efficient UCB Estimator forNon-linear Contextual Bandit.
CoRR, 2021

Adversarial Training with Rectified Rejection.
CoRR, 2021

Optimizing Information-theoretical Generalization Bound via Anisotropic Noise of SGLD.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Large Scale Private Learning via Low-rank Reparametrization.
Proceedings of the 38th International Conference on Machine Learning, 2021

Do not Let Privacy Overbill Utility: Gradient Embedding Perturbation for Private Learning.
Proceedings of the 9th International Conference on Learning Representations, 2021

How Does Data Augmentation Affect Privacy in Machine Learning?
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Convergence of Distributed Stochastic Variance Reduced Methods Without Sampling Extra Data.
IEEE Trans. Signal Process., 2020

Well-Conditioned Methods for Ill-Conditioned Systems: Linear Regression with Semi-Random Noise.
CoRR, 2020

Membership Inference with Privately Augmented Data Endorses the Benign while Suppresses the Adversary.
CoRR, 2020

Adai: Separating the Effects of Adaptive Learning Rate and Momentum Inertia.
CoRR, 2020

Gradient Perturbation is Underrated for Differentially Private Convex Optimization.
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

On Layer Normalization in the Transformer Architecture.
Proceedings of the 37th International Conference on Machine Learning, 2020

2019
Training Over-parameterized Deep ResNet Is almost as Easy as Training a Two-layer Network.
CoRR, 2019

BN-invariant Sharpness Regularizes the Training Model to Better Generalization.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

SGD Converges to Global Minimum in Deep Learning via Star-convex Path.
Proceedings of the 7th International Conference on Learning Representations, 2019

G-SGD: Optimizing ReLU Neural Networks in its Positively Scale-Invariant Space.
Proceedings of the 7th International Conference on Learning Representations, 2019

Capacity Control of ReLU Neural Networks by Basis-Path Norm.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
Median-Truncated Nonconvex Approach for Phase Retrieval With Outliers.
IEEE Trans. Inf. Theory, 2018

Train Feedfoward Neural Network with Layer-wise Adaptive Rate via Approximating Back-matching Propagation.
CoRR, 2018

Generalization Error Bounds with Probabilistic Guarantee for SGD in Nonconvex Optimization.
CoRR, 2018

On the Local Hessian in Back-propagation.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017
Multi-Key Generation Over a Cellular Model With a Helper.
IEEE Trans. Inf. Theory, 2017

A Nonconvex Approach for Phase Retrieval: Reshaped Wirtinger Flow and Incremental Algorithms.
J. Mach. Learn. Res., 2017

Block-diagonal Hessian-free Optimization for Training Neural Networks.
CoRR, 2017

Nonconvex Low-Rank Matrix Recovery with Arbitrary Outliers via Median-Truncated Gradient Descent.
CoRR, 2017

2016
Reshaped Wirtinger Flow for Solving Quadratic Systems of Equations.
CoRR, 2016

Reshaped Wirtinger Flow for Solving Quadratic System of Equations.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Provable Non-convex Phase Retrieval with Outliers: Median TruncatedWirtinger Flow.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Geometrical properties and accelerated gradient solvers of non-convex phase retrieval.
Proceedings of the 54th Annual Allerton Conference on Communication, 2016

On Compressive orthonormal Sensing.
Proceedings of the 54th Annual Allerton Conference on Communication, 2016

2015
Analysis of Robust PCA via Local Incoherence.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Two-key generation for a cellular model with a helper.
Proceedings of the IEEE International Symposium on Information Theory, 2015

Secret key capacity: Talk or keep silent?
Proceedings of the IEEE International Symposium on Information Theory, 2015

2014
The Capacity Region of the Source-Type Model for Secret Key and Private Key Generation.
IEEE Trans. Inf. Theory, 2014

Key capacity region for a cellular source model.
Proceedings of the 2014 IEEE Information Theory Workshop, 2014

Secret key-private key generation over three terminals: Capacity region.
Proceedings of the 2014 IEEE International Symposium on Information Theory, Honolulu, HI, USA, June 29, 2014

Helper-assisted asymmetric two key generation.
Proceedings of the 48th Asilomar Conference on Signals, Systems and Computers, 2014


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