Weijie Su
30 papers · 2014–2025 · 8 conferences · across top CS/AI conferences
Achievements
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π Conference Polyglot (8) π Interdisciplinary Bridge π§ Keyword Pioneer π£ Hot Topic Early Bird π Academic Marathon (11)
π
Renaissance Researcher
(7)
πΊοΈ
Taxonomy Completionist
(54)
π
Conference Polyglot
(8)
π
Triple Crown
π
Grand Slam
π
Keyword Champion
π
Century Club
(30)
π
Trend Setter
β‘
Prolific Year
(6)
ποΈ
Keyword Collector
(132)
π₯
Unstoppable
(7)
Conferences
NIPS (12)
ICML (6)
CVPR (4)
ICLR (3)
JMLR (2)
AAAI (1)
AISTATS (1)
COLT (1)
Top co-authors
Research topics
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 Nesterovβs Accelerated Gradient Method: Theory and Insights
NIPS 2014