ML Anthology

Li, Pan

82 publications

ICLR 2025 Convergent Privacy Loss of Noisy-SGD Without Convexity and Smoothness Eli Chien, Pan Li
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
NeurIPS 2025 Graph-KV: Breaking Sequence via Injecting Structural Biases into Large Language Models Haoyu Peter Wang, Peihao Wang, Mufei Li, Shikun Liu, Siqi Miao, Zhangyang Wang, Pan Li
JMLR 2025 Improving Graph Neural Networks on Multi-Node Tasks with the Labeling Trick Xiyuan Wang, Pan Li, Muhan Zhang
ICLR 2025 LayerDAG: A Layerwise Autoregressive Diffusion Model for Directed Acyclic Graph Generation Mufei Li, Viraj Shitole, Eli Chien, Changhai Man, Zhaodong Wang, Srinivas, Ying Zhang, Tushar Krishna, Pan Li
ICLRW 2025 LayerDAG: A Layerwise Autoregressive Diffusion Model for Directed Acyclic Graph Generation Mufei Li, Viraj Shitole, Eli Chien, Changhai Man, Zhaodong Wang, Srinivas, Ying Zhang, Tushar Krishna, Pan Li
IJCAI 2025 Optimal Distributed Training with Co-Adaptive Data Parallelism in Heterogeneous Environments Lifang Chen, Zhichao Chen, Liqi Yan, Yanyu Cheng, Fangli Guan, 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 Rethinking Addressing in Language Models via Contextualized Equivariant Positional Encoding Jiajun Zhu, Peihao Wang, Ruisi Cai, Jason D. Lee, Pan Li, Zhangyang Wang
IJCAI 2025 Risk-Aware Task Migration for Multiplex Unmanned Swarm Networks in Adversarial Environments Kai Di, Tienyu Zuo, Pan Li, Yuanshuang Jiang, Fulin Chen, Yichuan Jiang
NeurIPS 2025 RoFt-Mol: Benchmarking Robust Fine-Tuning with Molecular Graph Foundation Models Shikun Liu, Deyu Zou, Nima Shoghi, Victor Fung, Kai Liu, Pan Li
LoG 2025 Scalable and Efficient Temporal Graph Representation Learning via Forward Recent Sampling Yuhong Luo, Pan Li
ICLR 2025 Simple Is Effective: The Roles of Graphs and Large Language Models in Knowledge-Graph-Based Retrieval-Augmented Generation Mufei Li, Siqi Miao, Pan Li
ICLRW 2025 Simple Is Effective: The Roles of Graphs and Large Language Models in Knowledge-Graph-Based Retrieval-Augmented Generation Mufei Li, Siqi Miao, 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
ICLR 2025 Understanding and Mitigating Bottlenecks of State Space Models Through the Lens of Recency and Over-Smoothing Peihao Wang, Ruisi Cai, Yuehao Wang, Jiajun Zhu, Pragya Srivastava, Zhangyang Wang, Pan Li
ICLR 2025 What Are Good Positional Encodings for Directed Graphs? Yinan Huang, Haoyu Peter Wang, Pan Li
AAAI 2024 A Non-Parametric Graph Clustering Framework for Multi-View Data Shengju Yu, Siwei Wang, Zhibin Dong, Wenxuan Tu, Suyuan Liu, Zhao Lv, Pan Li, Miao Wang, En Zhu
NeurIPS 2024 Certified Machine Unlearning via Noisy Stochastic Gradient Descent Eli Chien, Haoyu Wang, Ziang Chen, Pan Li
TMLR 2024 DIG-MILP: A Deep Instance Generator for Mixed-Integer Linear Programming with Feasibility Guarantee Haoyu Peter Wang, Jialin Liu, Xiaohan Chen, Xinshang Wang, Pan Li, Wotao Yin
NeurIPS 2024 Differentially Private Graph Diffusion with Applications in Personalized PageRanks Rongzhe Wei, Eli Chien, Pan Li
NeurIPS 2024 GeSS: Benchmarking Geometric Deep Learning Under Scientific Applications with Distribution Shifts Deyu Zou, Shikun Liu, Siqi Miao, Victor Fung, Shiyu Chang, Pan Li
ICML 2024 Graph as Point Set Xiyuan Wang, Pan Li, Muhan Zhang
TMLR 2024 GraphMaker: Can Diffusion Models Generate Large Attributed Graphs? Mufei Li, Eleonora Kreacic, Vamsi K. Potluru, Pan Li
ICLRW 2024 Langevin Unlearning Eli Chien, Haoyu Peter Wang, Ziang Chen, Pan Li
NeurIPS 2024 Langevin Unlearning: A New Perspective of Noisy Gradient Descent for Machine Unlearning Eli Chien, Haoyu Wang, Ziang Chen, Pan Li
ICML 2024 Locality-Sensitive Hashing-Based Efficient Point Transformer with Applications in High-Energy Physics Siqi Miao, Zhiyuan Lu, Mia Liu, Javier Duarte, Pan Li
NeurIPS 2024 MSAGPT: Neural Prompting Protein Structure Prediction via MSA Generative Pre-Training Bo Chen, Zhilei Bei, Xingyi Cheng, Pan Li, Jie Tang, Le Song
ICMLW 2024 MSAGPT: Neural Prompting Protein Structure Prediction via MSA Generative Pre-Training Bo Chen, Zhilei Bei, Xingyi Cheng, Pan Li, Jie Tang, Le Song
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
ICLR 2024 On the Stability of Expressive Positional Encodings for Graphs Yinan Huang, William Lu, Joshua Robinson, Yu Yang, Muhan Zhang, Stefanie Jegelka, Pan Li
ICML 2024 Pairwise Alignment Improves Graph Domain Adaptation Shikun Liu, Deyu Zou, Han Zhao, Pan Li
ICLR 2024 Polynomial Width Is Sufficient for Set Representation with High-Dimensional Features Peihao Wang, Shenghao Yang, Shu Li, Zhangyang Wang, Pan Li
ICLR 2024 Towards Poisoning Fair Representations Tianci Liu, Haoyu Wang, Feijie Wu, Hengtong Zhang, Pan Li, Lu Su, Jing Gao
NeurIPS 2024 Training Compute-Optimal Protein Language Models Xingyi Cheng, Bo Chen, Pan Li, Jing Gong, Jie Tang, Le Song
ICMLW 2024 Training Compute-Optimal Protein Language Models Xingyi Cheng, Bo Chen, Pan Li, Jing Gong, Jie Tang, Le Song
ICMLW 2024 Training Compute-Optimal Protein Language Models Xingyi Cheng, Bo Chen, Pan Li, Jing Gong, Jie Tang, Le Song
NeurIPS 2023 Differentially Private Decoupled Graph Convolutions for Multigranular Topology Protection Eli Chien, Wei-Ning Chen, Chao Pan, Pan Li, Ayfer Ozgur, Olgica Milenkovic
ICLR 2023 Equivariant Hypergraph Diffusion Neural Operators Peihao Wang, Shenghao Yang, Yunyu Liu, Zhangyang Wang, Pan Li
ICCV 2023 Extensible and Efficient Proxy for Neural Architecture Search Yuhong Li, Jiajie Li, Cong Hao, Pan Li, Jinjun Xiong, Deming Chen
NeurIPSW 2023 GAD-EBM: Graph Anomaly Detection Using Energy-Based Models Amit Roy, Juan Shu, Olivier Elshocht, Jeroen Smeets, Ruqi Zhang, Pan Li
ICLR 2023 Interpretable Geometric Deep Learning via Learnable Randomness Injection Siqi Miao, Yunan Luo, Mia Liu, Pan Li
ICML 2023 Structural Re-Weighting Improves Graph Domain Adaptation Shikun Liu, Tianchun Li, Yongbin Feng, Nhan Tran, Han Zhao, Qiang Qiu, Pan Li
ICLR 2023 Unsupervised Learning for Combinatorial Optimization Needs Meta Learning Haoyu Peter Wang, Pan Li
CVPR 2022 Better Trigger Inversion Optimization in Backdoor Scanning Guanhong Tao, Guangyu Shen, Yingqi Liu, Shengwei An, Qiuling Xu, Shiqing Ma, Pan Li, Xiangyu Zhang
ICLR 2022 Equivariant and Stable Positional Encoding for More Powerful Graph Neural Networks Haorui Wang, Haoteng Yin, Muhan Zhang, Pan Li
ICLR 2022 Graph Auto-Encoder via Neighborhood Wasserstein Reconstruction Mingyue Tang, Pan Li, Carl Yang
NeurIPSW 2022 Interpretable Geometric Deep Learning via Learnable Randomness Injection Siqi Miao, Yunan Luo, Mia Liu, Pan Li
ICML 2022 Interpretable and Generalizable Graph Learning via Stochastic Attention Mechanism Siqi Miao, Mia Liu, Pan Li
LoG 2022 Neighborhood-Aware Scalable Temporal Network Representation Learning Yuhong Luo, Pan Li
CVPR 2022 Ranking Distance Calibration for Cross-Domain Few-Shot Learning Pan Li, Shaogang Gong, Chengjie Wang, Yanwei Fu
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
NeurIPS 2022 Unsupervised Learning for Combinatorial Optimization with Principled Objective Relaxation Haoyu Peter Wang, Nan Wu, Hang Yang, Cong Hao, Pan Li
ICCV 2021 A Simple Feature Augmentation for Domain Generalization Pan Li, Da Li, Wei Li, Shaogang Gong, Yanwei Fu, Timothy M. Hospedales
ICLR 2021 Adaptive Universal Generalized PageRank Graph Neural Network Eli Chien, Jianhao Peng, Pan Li, Olgica Milenkovic
NeurIPS 2021 Adversarial Graph Augmentation to Improve Graph Contrastive Learning Susheel Suresh, Pan Li, Cong Hao, Jennifer Neville
NeurIPS 2021 Generic Neural Architecture Search via Regression Yuhong Li, Cong Hao, Pan Li, Jinjun Xiong, Deming Chen
ICLR 2021 Inductive Representation Learning in Temporal Networks via Causal Anonymous Walks Yanbang Wang, Yen-Yu Chang, Yunyu Liu, Jure Leskovec, Pan Li
NeurIPS 2021 Labeling Trick: A Theory of Using Graph Neural Networks for Multi-Node Representation Learning Muhan Zhang, Pan Li, Yinglong Xia, Kai Wang, Long Jin
NeurIPS 2021 Local Hyper-Flow Diffusion Kimon Fountoulakis, Pan Li, Shenghao Yang
NeurIPS 2021 Nested Graph Neural Networks Muhan Zhang, Pan Li
IJCAI 2021 Regularising Knowledge Transfer by Meta Functional Learning Pan Li, Yanwei Fu, Shaogang Gong
NeurIPSW 2021 Semi-Supervised Graph Neural Network for Particle-Level Noise Removal Tianchun Li, Shikun Liu, Yongbin Feng, Nhan Tran, Miaoyuan Liu, Pan Li
ICCV 2021 Striking a Balance Between Stability and Plasticity for Class-Incremental Learning Guile Wu, Shaogang Gong, Pan Li
NeurIPS 2020 Distance Encoding: Design Provably More Powerful Neural Networks for Graph Representation Learning Pan Li, Yanbang Wang, Hongwei Wang, Jure Leskovec
NeurIPS 2020 Graph Information Bottleneck Tailin Wu, Hongyu Ren, Pan Li, Jure Leskovec
JMLR 2020 Quadratic Decomposable Submodular Function Minimization: Theory and Practice Pan Li, Niao He, Olgica Milenkovic
AISTATS 2019 $HS^2$: Active Learning over Hypergraphs with Pointwise and Pairwise Queries I Chien, Huozhi Zhou, Pan Li
NeurIPS 2019 Conditional Structure Generation Through Graph Variational Generative Adversarial Nets Carl Yang, Peiye Zhuang, Wenhan Shi, Alan Luu, Pan Li
ACML 2019 Differentially Private Community Detection in Attributed Social Networks Tianxi Ji, Changqing Luo, Yifan Guo, Jinlong Ji, Weixian Liao, Pan Li
IJCAI 2019 Learning to Learn Gradient Aggregation by Gradient Descent Jinlong Ji, Xuhui Chen, Qianlong Wang, Lixing Yu, Pan Li
NeurIPS 2019 Optimizing Generalized PageRank Methods for Seed-Expansion Community Detection Pan Li, I Chien, Olgica Milenkovic
AAAI 2018 Measuring the Popularity of Job Skills in Recruitment Market: A Multi-Criteria Approach Tong Xu, Hengshu Zhu, Chen Zhu, Pan Li, Hui Xiong
ACML 2018 Multidimensional Time Series Anomaly Detection: A GRU-Based Gaussian Mixture Variational Autoencoder Approach Yifan Guo, Weixian Liao, Qianlong Wang, Lixing Yu, Tianxi Ji, Pan Li
NeurIPS 2018 Quadratic Decomposable Submodular Function Minimization Pan Li, Niao He, Olgica Milenkovic
NeurIPS 2018 Revisiting Decomposable Submodular Function Minimization with Incidence Relations Pan Li, Olgica Milenkovic
ACML 2018 SecureNets: Secure Inference of Deep Neural Networks on an Untrusted Cloud Xuhui Chen, Jinlong Ji, Lixing Yu, Changqing Luo, Pan Li
ICML 2018 Submodular Hypergraphs: P-Laplacians, Cheeger Inequalities and Spectral Clustering Pan Li, Olgica Milenkovic
AISTATS 2017 Efficient Rank Aggregation via Lehmer Codes Pan Li, Arya Mazumdar, Olgica Milenkovic
NeurIPS 2017 Inhomogeneous Hypergraph Clustering with Applications Pan Li, Olgica Milenkovic