Hyperparameter-free DOA estimation under power constraints. - Chundi Zheng; Gang Li 008; Pan Li 005; Xiqin Wang (ICASSP, 2013)

A Feature Selection Method Based on the Sparse Multi-Class SVM for Fingerprinting Localization. - Pan Li 005; Huadong Meng; Xiqin Wang (VTC Fall, 2014)

On recovery of sparse signals with block structures. - Pan Li 005; Wei Dai 001; Huadong Meng; Xiqin Wang (ISIT, 2015)

Spectrally Efficient CSI Acquisition for Power Line Communications: A Bayesian Compressive Sensing Perspective. - Wenbo Ding 001; Yang Lu 007; Fang Yang 001; Wei Dai 001; Pan Li 005; Sicong Liu 002; Jian Song 004 (IEEE J. Sel. Areas Commun., 2016)

Efficient Rank Aggregation via Lehmer Codes. - Pan Li 005; Arya Mazumdar; Olgica Milenkovic (AISTATS, 2017)

Motif clustering and overlapping clustering for social network analysis. - Pan Li 005; Hoang Dau; Gregory J. Puleo; Olgica Milenkovic (INFOCOM, 2017)

Multiclass MinMax rank aggregation. - Pan Li 005; Olgica Milenkovic (ISIT, 2017)

Inhomogeneous Hypergraph Clustering with Applications. - Pan Li 005; Olgica Milenkovic (NIPS, 2017)

Meta-Graph Based HIN Spectral Embedding: Methods, Analyses, and Insights. - Carl Yang 001; Yichen Feng; Pan Li 005; Yu Shi 002; Jiawei Han 001 (ICDM, 2018)

Submodular Hypergraphs: p-Laplacians, Cheeger Inequalities and Spectral Clustering. - Pan Li 005; Olgica Milenkovic (ICML, 2018)

Quadratic Decomposable Submodular Function Minimization. - Pan Li 005; Niao He; Olgica Milenkovic (NeurIPS, 2018)

Revisiting Decomposable Submodular Function Minimization with Incidence Relations. - Pan Li 005; Olgica Milenkovic (NeurIPS, 2018)

HS2: Active Learning over Hypergraphs. - I (Eli) Chien; Huozhi Zhou; Pan Li 005 (CoRR, 2018)

HS2: Active learning over hypergraphs with pointwise and pairwise queries. - I (Eli) Chien; Huozhi Zhou; Pan Li 005 (AISTATS, 2019)

Combining Decision Trees and Neural Networks for Learning-to-Rank in Personal Search. - Pan Li 005; Zhen Qin 001; Xuanhui Wang; Donald Metzler (KDD, 2019)

Optimizing Generalized PageRank Methods for Seed-Expansion Community Detection. - Pan Li 005; I (Eli) Chien; Olgica Milenkovic (NeurIPS, 2019)

Conditional Structure Generation through Graph Variational Generative Adversarial Nets. - Carl Yang 001; Peiye Zhuang; Wenhan Shi; Alan Luu; Pan Li 005 (NeurIPS, 2019)

Learning on graphs with high-order relations: spectral methods, optimization and applications - Pan Li 005 (2019)

Distance Encoding: Design Provably More Powerful Neural Networks for Graph Representation Learning. - Pan Li 005; Yanbang Wang; Hongwei Wang 004; Jure Leskovec (NeurIPS, 2020)

Graph Information Bottleneck. - Tailin Wu; Hongyu Ren; Pan Li 005; Jure Leskovec (NeurIPS, 2020)

Joint Adaptive Feature Smoothing and Topology Extraction via Generalized PageRank GNNs. - Eli Chien; Jianhao Peng; Pan Li 005; Olgica Milenkovic (CoRR, 2020)

Distance Encoding - Design Provably More Powerful Graph Neural Networks for Structural Representation Learning. - Pan Li 005; Yanbang Wang; Hongwei Wang 004; Jure Leskovec (CoRR, 2020)

MStream: Fast Streaming Multi-Aspect Group Anomaly Detection. - Siddharth Bhatia 001; Arjit Jain; Pan Li 005; Ritesh Kumar; Bryan Hooi (CoRR, 2020)

Revisiting Graph Neural Networks for Link Prediction. - Muhan Zhang; Pan Li 005; Yinglong Xia; Kai Wang; Long Jin (CoRR, 2020)

Revisit graph neural networks and distance encoding in a practical view. - Haoteng Yin; Yanbang Wang; Pan Li 005 (CoRR, 2020)

Quadratic Decomposable Submodular Function Minimization: Theory and Practice. - Pan Li 005; Niao He; Olgica Milenkovic (J. Mach. Learn. Res., 2020)

Motif and Hypergraph Correlation Clustering. - Pan Li 005; Gregory J. Puleo; Olgica Milenkovic (IEEE Trans. Inf. Theory, 2020)

MELOPPR: Software/Hardware Co-design for Memory-efficient Low-latency Personalized PageRank. - Lixiang Li 003; Yao Chen 008; Zacharie Zirnheld; Pan Li 005; Cong Hao (DAC, 2021)

Heterogeneous Graph Neural Network with Distance Encoding. - Houye Ji; Cheng Yang 002; Chuan Shi 001; Pan Li 005 (ICDM, 2021)

Adaptive Universal Generalized PageRank Graph Neural Network. - Eli Chien; Jianhao Peng; Pan Li 005; Olgica Milenkovic (ICLR, 2021)

Inductive Representation Learning in Temporal Networks via Causal Anonymous Walks. - Yanbang Wang; Yen-Yu Chang; Yunyu Liu; Jure Leskovec; Pan Li 005 (ICLR, 2021)

Landing Probabilities of Random Walks for Seed-Set Expansion in Hypergraphs. - Eli Chien; Pan Li 005; Olgica Milenkovic (ITW, 2021)

Breaking the Limit of Graph Neural Networks by Improving the Assortativity of Graphs with Local Mixing Patterns. - Susheel Suresh; Vinith Budde; Jennifer Neville; Pan Li 005; Jianzhu Ma (KDD, 2021)

Bipartite Dynamic Representations for Abuse Detection. - Andrew Z. Wang; Rex Ying; Pan Li 005; Nikhil Rao 001; Karthik Subbian; Jure Leskovec (KDD, 2021)

Local Hyper-Flow Diffusion. - Kimon Fountoulakis; Pan Li 005; Shenghao Yang 002 (NeurIPS, 2021)

Generic Neural Architecture Search via Regression. - Yuhong Li; Cong Hao; Pan Li 005; Jinjun Xiong; Deming Chen (NeurIPS, 2021)

Adversarial Graph Augmentation to Improve Graph Contrastive Learning. - Susheel Suresh; Pan Li 005; Cong Hao; Jennifer Neville (NeurIPS, 2021)

Nested Graph Neural Networks. - Muhan Zhang; Pan Li 005 (NeurIPS, 2021)

Labeling Trick: A Theory of Using Graph Neural Networks for Multi-Node Representation Learning. - Muhan Zhang; Pan Li 005; Yinglong Xia; Kai Wang; Long Jin (NeurIPS, 2021)

F-FADE: Frequency Factorization for Anomaly Detection in Edge Streams. - Yen-Yu Chang; Pan Li 005; Rok Sosic; M. H. Afifi; Marco Schweighauser; Jure Leskovec (WSDM, 2021)

MStream: Fast Anomaly Detection in Multi-Aspect Streams. - Siddharth Bhatia 001; Arjit Jain; Pan Li 005; Ritesh Kumar; Bryan Hooi (WWW, 2021)

Strongly Local Hypergraph Diffusions for Clustering and Semi-supervised Learning. - Meng Liu 027; Nate Veldt; Haoyu Song 003; Pan Li 005; David F. Gleich (WWW, 2021)

TEDIC: Neural Modeling of Behavioral Patterns in Dynamic Social Interaction Networks. - Yanbang Wang; Pan Li 005; Chongyang Bai; Jure Leskovec (WWW, 2021)

Principled Hyperedge Prediction with Structural Spectral Features and Neural Networks. - Changlin Wan; Muhan Zhang; Wei Hao; Sha Cao; Pan Li 005; Chi Zhang 021 (CoRR, 2021)

Neural Higher-order Pattern (Motif) Prediction in Temporal Networks. - Yunyu Liu; Jianzhu Ma; Pan Li 005 (CoRR, 2021)

Program-to-Circuit: Exploiting GNNs for Program Representation and Circuit Translation. - Nan Wu; Huake He; Yuan Xie 001; Pan Li 005; Cong Hao (CoRR, 2021)

Applications and Techniques for Fast Machine Learning in Science. - Allison McCarn Deiana; Nhan Tran; Joshua Agar; Michaela Blott; Giuseppe Di Guglielmo; Javier M. Duarte; Philip C. Harris; Scott Hauck; Mia Liu; Mark S. Neubauer; Jennifer Ngadiuba; Seda Ogrenci Memik; et al. (CoRR, 2021)

On Positional and Structural Node Features for Graph Neural Networks on Non-attributed Graphs. - Hejie Cui; Zijie Lu; Pan Li 005; Carl Yang 001 (CIKM, 2022)

High-level synthesis performance prediction using GNNs: benchmarking, modeling, and advancing. - Nan Wu; Hang Yang; Yuan Xie 001; Pan Li 005; Cong Hao (DAC, 2022)

Graph Auto-Encoder via Neighborhood Wasserstein Reconstruction. - Mingyue Tang; Pan Li 005; Carl Yang 001 (ICLR, 2022)

Equivariant and Stable Positional Encoding for More Powerful Graph Neural Networks. - Haorui Wang; Haoteng Yin; Muhan Zhang; Pan Li 005 (ICLR, 2022)

Interpretable and Generalizable Graph Learning via Stochastic Attention Mechanism. - Siqi Miao 001; Mia Liu; Pan Li 005 (ICML, 2022)

4SDrug: Symptom-based Set-to-set Small and Safe Drug Recommendation. - Yanchao Tan; Chengjun Kong; Leisheng Yu; Pan Li 005; Chaochao Chen 001; Xiaolin Zheng; Vicki Hertzberg; Carl Yang 001 (KDD, 2022)

Neighborhood-Aware Scalable Temporal Network Representation Learning. - Yuhong Luo; Pan Li 005 (LoG, 2022)

Unsupervised Learning for Combinatorial Optimization with Principled Objective Relaxation. - Haoyu Wang 004; Nan Wu; Hang Yang; Cong Hao; Pan Li 005 (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 005 (NeurIPS, 2022)

Neural Predicting Higher-order Patterns in Temporal Networks. - Yunyu Liu; Jianzhu Ma; Pan Li 005 (WWW, 2022)

Interpretable and Generalizable Graph Learning via Stochastic Attention Mechanism. - Siqi Miao 001; Miaoyuan Liu; Pan Li 005 (CoRR, 2022)

Two-Dimensional Weisfeiler-Lehman Graph Neural Networks for Link Prediction. - Yang Hu; Xiyuan Wang; Zhouchen Lin; Pan Li 005; Muhan Zhang (CoRR, 2022)

Extensible Proxy for Efficient NAS. - Yuhong Li; Jiajie Li 002; Cong Han; Pan Li 005; Jinjun Xiong; Deming Chen (CoRR, 2022)

Federated Graph Representation Learning using Self-Supervision. - Susheel Suresh; Danny Godbout; Arko Mukherjee; Mayank Shrivastava; Jennifer Neville; Pan Li 005 (CoRR, 2022)

Graph Federated Learning with Hidden Representation Sharing. - Shuang Wu; Mingxuan Zhang; Yuantong Li; Carl Yang 001; Pan Li 005 (CoRR, 2022)

Algorithm and System Co-design for Efficient Subgraph-based Graph Representation Learning. - Haoteng Yin; Muhan Zhang; Yanbang Wang; Jianguo Wang 001; Pan Li 005 (Proc. VLDB Endow., 2022)

MobilePrune: Neural Network Compression via ℓ0 Sparse Group Lasso on the Mobile System. - Yubo Shao; Kaikai Zhao; Zhiwen Cao; Zhehao Peng; Xingang Peng; Pan Li 005; Yijie Wang; Jianzhu Ma (Sensors, 2022)

Extensible and Efficient Proxy for Neural Architecture Search. - Yuhong Li; Jiajie Li 002; Cong Hao; Pan Li 005; Jinjun Xiong; Deming Chen (ICCV, 2023)

Interpretable Geometric Deep Learning via Learnable Randomness Injection. - Siqi Miao 001; Yunan Luo; Mia Liu; Pan Li 005 (ICLR, 2023)

Unsupervised Learning for Combinatorial Optimization Needs Meta Learning. - Haoyu Peter Wang; Pan Li 005 (ICLR, 2023)

Equivariant Hypergraph Diffusion Neural Operators. - Peihao Wang; Shenghao Yang 002; Yunyu Liu; Zhangyang Wang; Pan Li 005 (ICLR, 2023)

Structural Re-weighting Improves Graph Domain Adaptation. - Shikun Liu; Tianchun Li; Yongbin Feng; Nhan Tran; Han Zhao 002; Qiang Qiu; Pan Li 005 (ICML, 2023)

Differentially Private Decoupled Graph Convolutions for Multigranular Topology Protection. - Eli Chien; Wei-Ning Chen; Chao Pan 003; Pan Li 005; Ayfer Özgür; Olgica Milenkovic (NeurIPS, 2023)

Expressive and Efficient Representation Learning for Ranking Links in Temporal Graphs. - Susheel Suresh; Mayank Shrivastava; Arko Mukherjee; Jennifer Neville; Pan Li 005 (WWW, 2023)

Improving Graph Neural Networks on Multi-node Tasks with Labeling Tricks. - Xiyuan Wang; Pan Li 005; Muhan Zhang (CoRR, 2023)

On the Stability of Expressive Positional Encodings for Graph Neural Networks. - Yinan Huang; William Lu; Joshua Robinson 001; Yu Yang; Muhan Zhang; Stefanie Jegelka; Pan Li 005 (CoRR, 2023)

GDL-DS: A Benchmark for Geometric Deep Learning under Distribution Shifts. - Deyu Zou; Shikun Liu; Siqi Miao 001; Victor Fung; Shiyu Chang; Pan Li 005 (CoRR, 2023)

DIG-MILP: a Deep Instance Generator for Mixed-Integer Linear Programming with Feasibility Guarantee. - Haoyu Wang 004; Jialin Liu 003; Xiaohan Chen; Xinshang Wang; Pan Li 005; Wotao Yin (CoRR, 2023)

On the Inherent Privacy Properties of Discrete Denoising Diffusion Models. - Rongzhe Wei; Eleonora Kreacic; Haoyu Wang 004; Haoteng Yin; Eli Chien; Vamsi K. Potluru; Pan Li 005 (CoRR, 2023)

ABKD: Graph Neural Network Compression with Attention-Based Knowledge Distillation. - Anshul Ahluwalia; Rohit Das; Payman Behnam; Alind Khare; Pan Li 005; Alexey Tumanov (CoRR, 2023)

High Pileup Particle Tracking with Object Condensation. - Kilian Lieret; Gage DeZoort; Devdoot Chatterjee; Jian Park; Siqi Miao 001; Pan Li 005 (CoRR, 2023)

SUREL+: Moving from Walks to Sets for Scalable Subgraph-based Graph Representation Learning. - Haoteng Yin; Muhan Zhang; Jianguo Wang 001; Pan Li 005 (Proc. VLDB Endow., 2023)

Towards Poisoning Fair Representations. - Tianci Liu 003; Haoyu Wang 004; Feijie Wu; Hengtong Zhang; Pan Li 005; Lu Su 001; Jing Gao 004 (ICLR, 2024)

On the Stability of Expressive Positional Encodings for Graphs. - Yinan Huang; William Lu; Joshua Robinson 001; Yu Yang; Muhan Zhang; Stefanie Jegelka; Pan Li 005 (ICLR, 2024)

Polynomial Width is Sufficient for Set Representation with High-dimensional Features. - Peihao Wang; Shenghao Yang 002; Shu Li; Zhangyang Wang; Pan Li 005 (ICLR, 2024)

Locality-Sensitive Hashing-Based Efficient Point Transformer with Applications in High-Energy Physics. - Siqi Miao 001; Zhiyuan Lu; Mia Liu; Javier M. Duarte; Pan Li 005 (ICML, 2024)

Pairwise Alignment Improves Graph Domain Adaptation. - Shikun Liu; Deyu Zou; Han Zhao 002; Pan Li 005 (ICML, 2024)

Graph As Point Set. - Xiyuan Wang; Pan Li 005; Muhan Zhang (ICML, 2024)

Scalable and Efficient Temporal Graph Representation Learning via Forward Recent Sampling. - Yuhong Luo; Pan Li 005 (LoG, 2024)

Certified Machine Unlearning via Noisy Stochastic Gradient Descent. - Eli Chien; Haoyu Wang 004; Ziang Chen; Pan Li 005 (NeurIPS, 2024)

Langevin Unlearning: A New Perspective of Noisy Gradient Descent for Machine Unlearning. - Eli Chien; Haoyu Wang 004; Ziang Chen; Pan Li 005 (NeurIPS, 2024)

Differentially Private Graph Diffusion with Applications in Personalized PageRanks. - Rongzhe Wei; Eli Chien; Pan Li 005 (NeurIPS, 2024)

GeSS: Benchmarking Geometric Deep Learning under Scientific Applications with Distribution Shifts. - Deyu Zou; Shikun Liu; Siqi Miao 001; Victor Fung; Shiyu Chang; Pan Li 005 (NeurIPS, 2024)

GAD-NR: Graph Anomaly Detection via Neighborhood Reconstruction. - Amit Roy; Juan Shu; Jia Li 009; Carl Yang 001; Olivier Elshocht; Jeroen Smeets; Pan Li 005 (WSDM, 2024)

Learning Scalable Structural Representations for Link Prediction with Bloom Signatures. - Tianyi Zhang 011; Haoteng Yin; Rongzhe Wei; Pan Li 005; Anshumali Shrivastava (WWW, 2024)

No Need to Look Back: An Efficient and Scalable Approach for Temporal Network Representation Learning. - Yuhong Luo; Pan Li 005 (CoRR, 2024)

Stochastic Gradient Langevin Unlearning. - Eli Chien; Haoyu Wang 004; Ziang Chen; Pan Li 005 (CoRR, 2024)

What Can We Learn from State Space Models for Machine Learning on Graphs? - Yinan Huang; Siqi Miao 001; Pan Li 005 (CoRR, 2024)

Towards Understanding Sensitive and Decisive Patterns in Explainable AI: A Case Study of Model Interpretation in Geometric Deep Learning. - Jiajun Zhu; Siqi Miao 001; Rex Ying; Pan Li 005 (CoRR, 2024)

A Benchmark on Directed Graph Representation Learning in Hardware Designs. - Haoyu Wang 004; Yinan Huang; Nan Wu; Pan Li 005 (CoRR, 2024)

Privately Learning from Graphs with Applications in Fine-tuning Large Language Models. - Haoteng Yin; Rongzhe Wei; Eli Chien; Pan Li 005 (CoRR, 2024)

LayerDAG: A Layerwise Autoregressive Diffusion Model for Directed Acyclic Graph Generation. - Mufei Li; Viraj Shitole; Eli Chien; Changhai Man; Zhaodong Wang; Srinivas Sridharan 002; Ying Zhang; Tushar Krishna; Pan Li 005 (CoRR, 2024)

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 005; Eli Chien (CoRR, 2024)

GraphMaker: Can Diffusion Models Generate Large Attributed Graphs? - Mufei Li; Eleonora Kreacic; Vamsi K. Potluru; Pan Li 005 (Trans. Mach. Learn. Res., 2024)

DIG-MILP: a Deep Instance Generator for Mixed-Integer Linear Programming with Feasibility Guarantee. - Haoyu Peter Wang; Jialin Liu 003; Xiaohan Chen; Xinshang Wang; Pan Li 005; Wotao Yin (Trans. Mach. Learn. Res., 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 005 (Trans. Mach. Learn. Res., 2024)

Distance Information Improves Heterogeneous Graph Neural Networks. - Chuan Shi 001; Houye Ji; Zhiyuan Lu; Ye Tang; Pan Li 005; Cheng Yang 002 (IEEE Trans. Knowl. Data Eng., 2024)

Ambiguities in neural-network-based hyperedge prediction. - Changlin Wan; Muhan Zhang; Pengtao Dang; Wei Hao; Sha Cao; Pan Li 005; Chi Zhang 021 (J. Appl. Comput. Topol., 2024)

Convergent Privacy Loss of Noisy-SGD without Convexity and Smoothness. - Eli Chien; Pan Li 005 (ICLR, 2025)

What Are Good Positional Encodings for Directed Graphs? - Yinan Huang; Haoyu Peter Wang; Pan Li 005 (ICLR, 2025)

Simple is Effective: The Roles of Graphs and Large Language Models in Knowledge-Graph-Based Retrieval-Augmented Generation. - Mufei Li; Siqi Miao 001; Pan Li 005 (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 005 (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 005 (ICLR, 2025)

Towards unveiling sensitive and decisive patterns in explainable AI with a case study in geometric deep learning. - Jiajun Zhu; Siqi Miao 001; Rex Ying; Pan Li 005 (Nat. Mac. Intell., 2025)

Rethinking Addressing in Language Models via Contexualized Equivariant Positional Encoding. - Jiajun Zhu; Peihao Wang; Ruisi Cai; Jason D. Lee; Pan Li 005; Zhangyang Wang (CoRR, 2025)

Model Generalization on Text Attribute Graphs: Principles with Large Language Models. - Haoyu Wang 004; Shikun Liu; Rongzhe Wei; Pan Li 005 (CoRR, 2025)

Towards A Universal Graph Structural Encoder. - Jialin Chen; Haolan Zuo; Haoyu Peter Wang; Siqi Miao 001; Pan Li 005; Rex Ying (CoRR, 2025)

Privacy Amplification in Differentially Private Zeroth-Order Optimization with Hidden States. - Eli Chien; Wei-Ning Chen; Pan Li 005 (CoRR, 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 005 (CoRR, 2025)

Graph-KV: Breaking Sequence via Injecting Structural Biases into Large Language Models. - Haoyu Wang 004; Peihao Wang; Mufei Li; Shikun Liu; Siqi Miao 001; Zhangyang Wang; Pan Li 005 (CoRR, 2025)

Powers of Magnetic Graph Matrix: Fourier Spectrum, Walk Compression, and Applications. - Yinan Huang; David F. Gleich; Pan Li 005 (CoRR, 2025)

Differentially Private Relational Learning with Entity-level Privacy Guarantees. - Yinan Huang; Haoteng Yin; Eli Chien; Rongzhe Wei; Pan Li 005 (CoRR, 2025)

Weak-to-Strong GraphRAG: Aligning Weak Retrievers with Large Language Models for Graph-based Retrieval Augmented Generation. - Deyu Zou; Yongqiang Chen; Mufei Li; Siqi Miao 001; Chenxi Liu; Bo Han; James Cheng; Pan Li 005 (CoRR, 2025)