Wei, Rongzhe

9 publications

NeurIPS 2025 Differentially Private Relational Learning with Entity-Level Privacy Guarantees Yinan Huang, Haoteng Yin, Eli Chien, Rongzhe Wei, Pan Li

NeurIPS 2025 Do LLMs Really Forget? Evaluating Unlearning with Knowledge Correlation and Confidence Awareness Rongzhe Wei, Peizhi Niu, Hans Hao-Hsun Hsu, Ruihan Wu, Haoteng Yin, Mohsen Ghassemi, Yifan Li, Vamsi K. Potluru, Eli Chien, Kamalika Chaudhuri, Olgica Milenkovic, Pan Li

ICML 2025 Generalization Principles for Inference over Text-Attributed Graphs with Large Language Models Haoyu Peter Wang, Shikun Liu, Rongzhe Wei, Pan Li

ICLRW 2025 Privately Learning from Graphs with Applications in Fine-Tuning Large Pretrained Models Haoteng Yin, Rongzhe Wei, Eli Chien, Pan Li

ICML 2025 Underestimated Privacy Risks for Minority Populations in Large Language Model Unlearning Rongzhe Wei, Mufei Li, Mohsen Ghassemi, Eleonora Kreacic, Yifan Li, Xiang Yue, Bo Li, Vamsi K. Potluru, Pan Li, Eli Chien

NeurIPS 2024 Differentially Private Graph Diffusion with Applications in Personalized PageRanks Rongzhe Wei, Eli Chien, Pan Li

ICLRW 2024 Guarding Multiple Secrets: Enhanced Summary Statistic Privacy for Data Sharing Shuaiqi Wang, Rongzhe Wei, Mohsen Ghassemi, Eleonora Kreacic, Vamsi K. Potluru

TMLR 2024 On the Inherent Privacy Properties of Discrete Denoising Diffusion Models Rongzhe Wei, Eleonora Kreacic, Haoyu Peter Wang, Haoteng Yin, Eli Chien, Vamsi K. Potluru, Pan Li

NeurIPS 2022 Understanding Non-Linearity in Graph Neural Networks from the Bayesian-Inference Perspective Rongzhe Wei, Haoteng Yin, Junteng Jia, Austin R Benson, Pan Li