← Authors

Weijie Su

30 papers · 2014–2025 · 8 conferences · across top CS/AI conferences

Achievements

πŸƒ Academic Marathon (11) 🐝 Cross-Pollinator (12) πŸŒ‰ Interdisciplinary Bridge 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🌈 Renaissance Researcher (7) πŸ—ΊοΈ Taxonomy Completionist (54) 🌍 Conference Polyglot (8) πŸ‘‘ Triple Crown πŸ† Grand Slam πŸ† Keyword Champion πŸ’Ž Century Club (30) πŸ“ˆ Trend Setter ⚑ Prolific Year (6) πŸ—ƒοΈ Keyword Collector (132) πŸ”₯ Unstoppable (7)

Conferences

NIPS (12) ICML (6) CVPR (4) ICLR (3) JMLR (2) AAAI (1) AISTATS (1) COLT (1)

Top co-authors

Xizhou Zhu (8) Jifeng Dai (8) Bin Li (6) Lewei Lu (6) Hangfeng He (4) Wenhai Wang (4) Yu Qiao (4) Jie Zhou (3) Hua Wang (3) Xiaogang Wang (3)

Research topics

Differential Privacy (3) Probability (1)

Keywords

convex optimization (4) stochastic gradient descent (4) differential privacy (4) representation learning (3) differential equation (3) gradient descent (3) neural network (2) gaussian differential privacy (2) adversarial robustness (2) convergence rate (2) incentive compatibility (2) high-dimensional regression (2) accelerated gradient method (2) peer review (2) visual representation (2) accelerated gradient (2) self-supervised learning (2) vision-language model (2) nonconvex optimization (1) variable selection (1)

Papers

CoMemo: LVLMs Need Image Context with Image Memory ICML 2025
PVC: Progressive Visual Token Compression for Unified Image and Video Processing in Large Vision-Language Models CVPR 2025
Vision Model Pre-training on Interleaved Image-Text Data via Latent Compression Learning NIPS 2024
InternVL: Scaling up Vision Foundation Models and Aligning for Generic Visual-Linguistic Tasks CVPR 2024
Bridging the Gap: Rademacher Complexity in Robust and Standard Generalization COLT 2024
Eliciting Honest Information from Authors Using Sequential Review AAAI 2024
On Learning Rates and SchrΓΆdinger Operators JMLR 2023
DP-HyPO: An Adaptive Private Framework for Hyperparameter Optimization NIPS 2023
Unified Enhancement of Privacy Bounds for Mixture Mechanisms via $f$-Differential Privacy NIPS 2023
Towards All-in-One Pre-Training via Maximizing Multi-Modal Mutual Information CVPR 2023
Siamese Image Modeling for Self-Supervised Vision Representation Learning CVPR 2023
The alignment property of SGD noise and how it helps select flat minima: A stability analysis NIPS 2022
ROCK: Causal Inference Principles for Reasoning about Commonsense Causality ICML 2022
Toward Better Generalization Bounds with Locally Elastic Stability ICML 2021
Oneshot Differentially Private Top-k Selection ICML 2021
Federated f-Differential Privacy AISTATS 2021
You Are the Best Reviewer of Your Own Papers: An Owner-Assisted Scoring Mechanism NIPS 2021
A Central Limit Theorem for Differentially Private Query Answering NIPS 2021
Imitating Deep Learning Dynamics via Locally Elastic Stochastic Differential Equations NIPS 2021
Deformable DETR: Deformable Transformers for End-to-End Object Detection ICLR 2021
VL-BERT: Pre-training of Generic Visual-Linguistic Representations ICLR 2020
The Complete Lasso Tradeoff Diagram NIPS 2020
Label-Aware Neural Tangent Kernel: Toward Better Generalization and Local Elasticity NIPS 2020
The Local Elasticity of Neural Networks ICLR 2020
Towards Understanding the Dynamics of the First-Order Adversaries ICML 2020
Sharp Composition Bounds for Gaussian Differential Privacy via Edgeworth Expansion ICML 2020
Acceleration via Symplectic Discretization of High-Resolution Differential Equations NIPS 2019
Algorithmic Analysis and Statistical Estimation of SLOPE via Approximate Message Passing NIPS 2019
A Differential Equation for Modeling Nesterov's Accelerated Gradient Method: Theory and Insights JMLR 2016
A Differential Equation for Modeling Nesterov’s Accelerated Gradient Method: Theory and Insights NIPS 2014