Huishuai Zhang
42 papers · 2015–2026 · 12 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
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πΊοΈ Taxonomy Completionist (72) π Conference Polyglot Β· Gold π Academic Marathon Β· Half π Interdisciplinary Bridge Β· Silver π£ Hot Topic Early Bird
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(13)
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(15)
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Keyword Champion
(3)
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Keyword Pioneer
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Triple Crown
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Renaissance Researcher
(5)
π₯
Unstoppable Β· Silver
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(2)
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Prolific Year Β· Productive
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Conference Pioneer
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Century Club Β· Bronze
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Trend Setter
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Keyword Collector
(197)
Venues
Top co-authors
Research topics
Machine Learning
(33)
Optimization & Theory Β· Machine Learning
(21)
Deep Learning
(19)
Artificial Intelligence
(15)
Core AI
(11)
Learning Types Β· Machine Learning
(10)
Application Areas
(9)
Mathematics & Optimization
(7)
Learning Types Β· Deep Learning
(7)
Optimization & Theory Β· Deep Learning
(7)
Architectures
(6)
Optimization
(6)
Natural Language Processing
(5)
Techniques
(5)
Security & Privacy
(4)
Keywords
differential privacy
(6)
neural network
(5)
gradient descent
(5)
large language model
(5)
generalization bound
(4)
stochastic gradient descent
(4)
non-convex optimization
(4)
phase retrieval
(3)
wirtinger flow
(3)
learning rate
(3)
neural network optimization
(3)
adam optimizer
(2)
adversarial example
(2)
privacy budget
(2)
privacy attack
(2)
privacy risk
(2)
deep learning
(2)
few-shot learning
(2)
robust classification
(2)
convex optimization
(2)
Papers
Conditional Memory via Scalable Lookup: A New Axis of Sparsity for Large Language Models
ACL 2026
De-Anonymization at Scale via Tournament-Style Attribution
ACL 2026
AdamS: Momentum Itself Can Be A Normalizer for LLM Pretraining and Post-training
EMNLP 2025
Efficient Domain Continual pretraining by Mitigating the Stability Gap
ACL 2025
English as Defense Proxy: Mitigating Multilingual Jailbreak via Eliciting English Safety Knowledge
EMNLP 2025
Latent Preference Coding: Aligning Large Language Models via Discrete Latent Codes
ICML 2025
ReasVQA: Advancing VideoQA with Imperfect Reasoning Process
NAACL 2025
ReMamba: Equip Mamba with Effective Long-Sequence Modeling
EMNLP 2025
Understanding Nonlinear Implicit Bias via Region Counts in Input Space
ICML 2025
Understanding Visual Detail Hallucinations of Large Vision-Language Models
IJCAI 2025
VideoLLM Knows When to Speak: Enhancing Time-Sensitive Video Comprehension with Video-Text Duet Interaction Format
EMNLP 2025
Differentially Private Synthetic Data via Foundation Model APIs 2: Text
ICML 2024
Mixture-of-Modules: Reinventing Transformers as Dynamic Assemblies of Modules
EMNLP 2024
xRAG: Extreme Context Compression for Retrieval-augmented Generation with One Token
NeurIPS 2024
Adversarial Noises Are Linearly Separable for (Nearly) Random Neural Networks
AISTATS 2023
Closing the gap between the upper bound and lower bound of Adam's iteration complexity
NeurIPS 2023
Convergence of AdaGrad for Non-convex Objectives: Simple Proofs and Relaxed Assumptions
COLT 2023
Denoising Masked Autoencoders Help Robust Classification
ICLR 2023
DiffKendall: A Novel Approach for Few-Shot Learning with Differentiable Kendall's Rank Correlation
NeurIPS 2023
Exploring the Limits of Differentially Private Deep Learning with Group-wise Clipping
ICLR 2023
FD-Align: Feature Discrimination Alignment for Fine-tuning Pre-Trained Models in Few-Shot Learning
NeurIPS 2023
On the Generalization Properties of Diffusion Models
NeurIPS 2023
Similarity Distribution Based Membership Inference Attack on Person Re-identification
AAAI 2023
Adaptive Inertia: Disentangling the Effects of Adaptive Learning Rate and Momentum
ICML 2022
Differentially Private Fine-tuning of Language Models
ICLR 2022
Does Momentum Change the Implicit Regularization on Separable Data?
NeurIPS 2022
Two Coupled Rejection Metrics Can Tell Adversarial Examples Apart
CVPR 2022
Do not Let Privacy Overbill Utility: Gradient Embedding Perturbation for Private Learning
ICLR 2021
How Does Data Augmentation Affect Privacy in Machine Learning?
AAAI 2021
Large Scale Private Learning via Low-rank Reparametrization
ICML 2021
Optimizing Information-theoretical Generalization Bound via Anisotropic Noise of SGLD
NeurIPS 2021
Gradient Perturbation is Underrated for Differentially Private Convex Optimization
IJCAI 2020
On Layer Normalization in the Transformer Architecture
ICML 2020
BN-invariant Sharpness Regularizes the Training Model to Better Generalization
IJCAI 2019
Capacity Control of ReLU Neural Networks by Basis-Path Norm
AAAI 2019
G-SGD: Optimizing ReLU Neural Networks in its Positively Scale-Invariant Space
ICLR 2019
SGD Converges to Global Minimum in Deep Learning via Star-convex Path
ICLR 2019
On the Local Hessian in Back-propagation
NeurIPS 2018
A Nonconvex Approach for Phase Retrieval: Reshaped Wirtinger Flow and Incremental Algorithms
JMLR 2017
Provable Non-convex Phase Retrieval with Outliers: Median TruncatedWirtinger Flow
ICML 2016
Reshaped Wirtinger Flow for Solving Quadratic System of Equations
NeurIPS 2016
Analysis of Robust PCA via Local Incoherence
NeurIPS 2015