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Pan Li 0005
李攀
Person information
- unicode name: 李攀
- affiliation: Georgia Institute of Technology, GA, USA
- affiliation (former): Purdue University, Department of Computer Science, West Lafayette, IN, USA
- affiliation (former): Stanford University, CA, USA
- affiliation (former): University of Illinois at Urbana-Champaign, Champaign, IL, USA
- affiliation (former): Tsinghua University, China
Other persons with the same name
- Pan Li — disambiguation page
- Pan Li 0001
— Case Western Reserve University, Department of Electrical Engineering and Computer Science, Cleveland, OH, USA (and 2 more)
- Pan Li 0002 — University of Leeds, School of Earth and Environment, UK
- Pan Li 0003 — Henan University of Technology, College of Information Science and Engineering, China
- Pan Li 0004 — University of Washington, Seattle, WA, USA
- Pan Li 0006
- Pan Li 0007 — Baidu Talent Intelligence Center, Baidu Inc., China (and 1 more)
- Pan Li 0008
- Pan Li 0010
- Pan Li 0011 — China University of Mining and Technology, Xuzhou, China
- Pan Li 0012 — Wuhan University, Wuhan, China (and 1 more)
- Pan Li 0013
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2020 – today
- 2024
- [j9]Changlin Wan, Muhan Zhang, Pengtao Dang, Wei Hao, Sha Cao, Pan Li, Chi Zhang:
Ambiguities in neural-network-based hyperedge prediction. J. Appl. Comput. Topol. 8(5): 1333-1361 (2024) - [j8]Chuan Shi
Distance Information Improves Heterogeneous Graph Neural Networks. IEEE Trans. Knowl. Data Eng. 36(3): 1030-1043 (2024) - [j7]Rongzhe Wei, Eleonora Kreacic, Haoyu Peter Wang, Haoteng Yin, Eli Chien, Vamsi K. Potluru, Pan Li:
On the Inherent Privacy Properties of Discrete Denoising Diffusion Models. Trans. Mach. Learn. Res. 2024 (2024) - [c58]Tianci Liu, Haoyu Wang, Feijie Wu, Hengtong Zhang, Pan Li, Lu Su, Jing Gao:
Towards Poisoning Fair Representations. ICLR 2024 - [c57]Yinan Huang, William Lu, Joshua Robinson, Yu Yang, Muhan Zhang, Stefanie Jegelka, Pan Li:
On the Stability of Expressive Positional Encodings for Graphs. ICLR 2024 - [c56]Peihao Wang, Shenghao Yang, Shu Li, Zhangyang Wang, Pan Li:
Polynomial Width is Sufficient for Set Representation with High-dimensional Features. ICLR 2024 - [c55]Siqi Miao, Zhiyuan Lu, Mia Liu, Javier M. Duarte, Pan Li:
Locality-Sensitive Hashing-Based Efficient Point Transformer with Applications in High-Energy Physics. ICML 2024 - [c54]Shikun Liu, Deyu Zou, Han Zhao, Pan Li:
Pairwise Alignment Improves Graph Domain Adaptation. ICML 2024 - [c53]Xiyuan Wang, Pan Li, Muhan Zhang:
Graph As Point Set. ICML 2024 - [c52]Amit Roy
GAD-NR: Graph Anomaly Detection via Neighborhood Reconstruction. WSDM 2024: 576-585 - [c51]Tianyi Zhang
Learning Scalable Structural Representations for Link Prediction with Bloom Signatures. WWW 2024: 980-991 - [i74]Eli Chien, Haoyu Wang, Ziang Chen, Pan Li:
Langevin Unlearning: A New Perspective of Noisy Gradient Descent for Machine Unlearning. CoRR abs/2401.10371 (2024) - [i73]Yuhong Luo, Pan Li:
No Need to Look Back: An Efficient and Scalable Approach for Temporal Network Representation Learning. CoRR abs/2402.01964 (2024) - [i72]Siqi Miao, Zhiyuan Lu, Mia Liu, Javier M. Duarte, Pan Li:
Locality-Sensitive Hashing-Based Efficient Point Transformer with Applications in High-Energy Physics. CoRR abs/2402.12535 (2024) - [i71]Shikun Liu, Deyu Zou, Han Zhao, Pan Li:
Pairwise Alignment Improves Graph Domain Adaptation. CoRR abs/2403.01092 (2024) - [i70]Eli Chien, Haoyu Wang, Ziang Chen, Pan Li:
Stochastic Gradient Langevin Unlearning. CoRR abs/2403.17105 (2024) - [i69]Xiyuan Wang, Pan Li, Muhan Zhang:
Graph as Point Set. CoRR abs/2405.02795 (2024) - [i68]Yinan Huang, Siqi Miao, Pan Li:
What Can We Learn from State Space Models for Machine Learning on Graphs? CoRR abs/2406.05815 (2024) - [i67]Rongzhe Wei, Eli Chien, Pan Li:
Differentially Private Graph Diffusion with Applications in Personalized PageRanks. CoRR abs/2407.00077 (2024) - [i66]Jiajun Zhu, Siqi Miao, Rex Ying, Pan Li:
Towards Understanding Sensitive and Decisive Patterns in Explainable AI: A Case Study of Model Interpretation in Geometric Deep Learning. CoRR abs/2407.00849 (2024) - [i65]Eli Chien, Pan Li:
Convergent Privacy Loss of Noisy-SGD without Convexity and Smoothness. CoRR abs/2410.01068 (2024) - [i64]Haoyu Wang, Yinan Huang, Nan Wu, Pan Li:
A Benchmark on Directed Graph Representation Learning in Hardware Designs. CoRR abs/2410.06460 (2024) - [i63]Haoteng Yin, Rongzhe Wei, Eli Chien, Pan Li:
Privately Learning from Graphs with Applications in Fine-tuning Large Language Models. CoRR abs/2410.08299 (2024) - 2023
- [j6]Haoteng Yin
SUREL+: Moving from Walks to Sets for Scalable Subgraph-based Graph Representation Learning. Proc. VLDB Endow. 16(11): 2939-2948 (2023) - [c50]Yuhong Li, Jiajie Li, Cong Hao, Pan Li, Jinjun Xiong, Deming Chen:
Extensible and Efficient Proxy for Neural Architecture Search. ICCV 2023: 6176-6187 - [c49]Siqi Miao, Yunan Luo, Mia Liu, Pan Li:
Interpretable Geometric Deep Learning via Learnable Randomness Injection. ICLR 2023 - [c48]Haoyu Peter Wang, Pan Li:
Unsupervised Learning for Combinatorial Optimization Needs Meta Learning. ICLR 2023 - [c47]Peihao Wang, Shenghao Yang, Yunyu Liu, Zhangyang Wang, Pan Li:
Equivariant Hypergraph Diffusion Neural Operators. ICLR 2023 - [c46]Shikun Liu, Tianchun Li, Yongbin Feng, Nhan Tran, Han Zhao, Qiang Qiu, Pan Li:
Structural Re-weighting Improves Graph Domain Adaptation. ICML 2023: 21778-21793 - [c45]Eli Chien, Wei-Ning Chen, Chao Pan, Pan Li, Ayfer Özgür, Olgica Milenkovic:
Differentially Private Decoupled Graph Convolutions for Multigranular Topology Protection. NeurIPS 2023 - [c44]Susheel Suresh
Expressive and Efficient Representation Learning for Ranking Links in Temporal Graphs. WWW 2023: 567-577 - [i62]Haoteng Yin, Muhan Zhang, Jianguo Wang, Pan Li:
SUREL+: Moving from Walks to Sets for Scalable Subgraph-based Graph Representation Learning. CoRR abs/2303.03379 (2023) - [i61]Xiyuan Wang, Pan Li, Muhan Zhang:
Improving Graph Neural Networks on Multi-node Tasks with Labeling Tricks. CoRR abs/2304.10074 (2023) - [i60]Amit Roy, Juan Shu, Jia Li, Carl Yang, Olivier Elshocht, Jeroen Smeets, Pan Li:
GAD-NR: Graph Anomaly Detection via Neighborhood Reconstruction. CoRR abs/2306.01951 (2023) - [i59]Shikun Liu, Tianchun Li, Yongbin Feng, Nhan Tran, Han Zhao, Qiu Qiang, Pan Li:
Structural Re-weighting Improves Graph Domain Adaptation. CoRR abs/2306.03221 (2023) - [i58]Peihao Wang, Shenghao Yang, Shu Li, Zhangyang Wang, Pan Li:
Polynomial Width is Sufficient for Set Representation with High-dimensional Features. CoRR abs/2307.04001 (2023) - [i57]Eli Chien, Wei-Ning Chen, Chao Pan, Pan Li, Ayfer Özgür, Olgica Milenkovic:
Differentially Private Decoupled Graph Convolutions for Multigranular Topology Protection. CoRR abs/2307.06422 (2023) - [i56]Tianci Liu, Haoyu Wang, Feijie Wu, Hengtong Zhang, Pan Li, Lu Su, Jing Gao:
Towards Poisoning Fair Representations. CoRR abs/2309.16487 (2023) - [i55]Yinan Huang, William Lu, Joshua Robinson, Yu Yang, Muhan Zhang, Stefanie Jegelka, Pan Li:
On the Stability of Expressive Positional Encodings for Graph Neural Networks. CoRR abs/2310.02579 (2023) - [i54]Deyu Zou, Shikun Liu, Siqi Miao, Victor Fung, Shiyu Chang, Pan Li:
GDL-DS: A Benchmark for Geometric Deep Learning under Distribution Shifts. CoRR abs/2310.08677 (2023) - [i53]Haoyu Wang, Jialin Liu, Xiaohan Chen, Xinshang Wang, Pan Li, Wotao Yin:
DIG-MILP: a Deep Instance Generator for Mixed-Integer Linear Programming with Feasibility Guarantee. CoRR abs/2310.13261 (2023) - [i52]Mufei Li, Eleonora Kreacic, Vamsi K. Potluru, Pan Li:
GraphMaker: Can Diffusion Models Generate Large Attributed Graphs? CoRR abs/2310.13833 (2023) - [i51]Rongzhe Wei, Eleonora Kreacic, Haoyu Wang, Haoteng Yin, Eli Chien, Vamsi K. Potluru, Pan Li:
On the Inherent Privacy Properties of Discrete Denoising Diffusion Models. CoRR abs/2310.15524 (2023) - [i50]Anshul Ahluwalia, Rohit Das, Payman Behnam, Alind Khare, Pan Li, Alexey Tumanov:
ABKD: Graph Neural Network Compression with Attention-Based Knowledge Distillation. CoRR abs/2310.15938 (2023) - [i49]Kilian Lieret, Gage DeZoort, Devdoot Chatterjee, Jian Park, Siqi Miao, Pan Li:
High Pileup Particle Tracking with Object Condensation. CoRR abs/2312.03823 (2023) - [i48]Tianyi Zhang, Haoteng Yin, Rongzhe Wei, Pan Li, Anshumali Shrivastava:
Learning Scalable Structural Representations for Link Prediction with Bloom Signatures. CoRR abs/2312.16784 (2023) - 2022
- [j5]Haoteng Yin
Algorithm and System Co-design for Efficient Subgraph-based Graph Representation Learning. Proc. VLDB Endow. 15(11): 2788-2796 (2022) - [j4]Yubo Shao
MobilePrune: Neural Network Compression via ℓ0 Sparse Group Lasso on the Mobile System. Sensors 22(11): 4081 (2022) - [c43]Hejie Cui
On Positional and Structural Node Features for Graph Neural Networks on Non-attributed Graphs. CIKM 2022: 3898-3902 - [c42]Nan Wu
High-level synthesis performance prediction using GNNs: benchmarking, modeling, and advancing. DAC 2022: 49-54 - [c41]Mingyue Tang, Pan Li, Carl Yang:
Graph Auto-Encoder via Neighborhood Wasserstein Reconstruction. ICLR 2022 - [c40]Haorui Wang, Haoteng Yin, Muhan Zhang, Pan Li:
Equivariant and Stable Positional Encoding for More Powerful Graph Neural Networks. ICLR 2022 - [c39]Siqi Miao, Mia Liu, Pan Li:
Interpretable and Generalizable Graph Learning via Stochastic Attention Mechanism. ICML 2022: 15524-15543 - [c38]Yanchao Tan, Chengjun Kong, Leisheng Yu, Pan Li, Chaochao Chen, Xiaolin Zheng, Vicki Hertzberg, Carl Yang:
4SDrug: Symptom-based Set-to-set Small and Safe Drug Recommendation. KDD 2022: 3970-3980 - [c37]Yuhong Luo, Pan Li:
Neighborhood-Aware Scalable Temporal Network Representation Learning. LoG 2022: 1 - [c36]Haoyu Wang, Nan Wu, Hang Yang, Cong Hao, Pan Li:
Unsupervised Learning for Combinatorial Optimization with Principled Objective Relaxation. NeurIPS 2022 - [c35]Rongzhe Wei, Haoteng Yin, Junteng Jia, Austin R. Benson, Pan Li:
Understanding Non-linearity in Graph Neural Networks from the Bayesian-Inference Perspective. NeurIPS 2022 - [c34]Yunyu Liu, Jianzhu Ma, Pan Li:
Neural Predicting Higher-order Patterns in Temporal Networks. WWW 2022: 1340-1351 - [i47]Nan Wu, Hang Yang, Yuan Xie, Pan Li, Cong Hao:
High-Level Synthesis Performance Prediction using GNNs: Benchmarking, Modeling, and Advancing. CoRR abs/2201.06848 (2022) - [i46]Siqi Miao, Miaoyuan Liu, Pan Li:
Interpretable and Generalizable Graph Learning via Stochastic Attention Mechanism. CoRR abs/2201.12987 (2022) - [i45]Mingyue Tang, Carl Yang, Pan Li:
Graph Auto-Encoder Via Neighborhood Wasserstein Reconstruction. CoRR abs/2202.09025 (2022) - [i44]Haoteng Yin, Muhan Zhang, Yanbang Wang, Jianguo Wang, Pan Li:
Algorithm and System Co-design for Efficient Subgraph-based Graph Representation Learning. CoRR abs/2202.13538 (2022) - [i43]Haorui Wang, Haoteng Yin, Muhan Zhang, Pan Li:
Equivariant and Stable Positional Encoding for More Powerful Graph Neural Networks. CoRR abs/2203.00199 (2022) - [i42]Yang Hu, Xiyuan Wang, Zhouchen Lin, Pan Li, Muhan Zhang:
Two-Dimensional Weisfeiler-Lehman Graph Neural Networks for Link Prediction. CoRR abs/2206.09567 (2022) - [i41]Haoyu Wang, Nan Wu, Hang Yang, Cong Hao, Pan Li:
Unsupervised Learning for Combinatorial Optimization with Principled Objective Relaxation. CoRR abs/2207.05984 (2022) - [i40]Peihao Wang, Shenghao Yang, Yunyu Liu, Zhangyang Wang, Pan Li:
Equivariant Hypergraph Diffusion Neural Operators. CoRR abs/2207.06680 (2022) - [i39]Rongzhe Wei, Haoteng Yin, Junteng Jia, Austin R. Benson, Pan Li:
Understanding Non-linearity in Graph Neural Networks from the Bayesian-Inference Perspective. CoRR abs/2207.11311 (2022) - [i38]Yuhong Luo, Pan Li:
Neighborhood-aware Scalable Temporal Network Representation Learning. CoRR abs/2209.01084 (2022) - [i37]Yuhong Li, Jiajie Li, Cong Han, Pan Li, Jinjun Xiong
Extensible Proxy for Efficient NAS. CoRR abs/2210.09459 (2022) - [i36]Susheel Suresh, Danny Godbout, Arko Mukherjee, Mayank Shrivastava, Jennifer Neville, Pan Li:
Federated Graph Representation Learning using Self-Supervision. CoRR abs/2210.15120 (2022) - [i35]Siqi Miao, Yunan Luo, Mia Liu, Pan Li:
Interpretable Geometric Deep Learning via Learnable Randomness Injection. CoRR abs/2210.16966 (2022) - [i34]Shuang Wu, Mingxuan Zhang, Yuantong Li, Carl Yang, Pan Li:
Graph Federated Learning with Hidden Representation Sharing. CoRR abs/2212.12158 (2022) - 2021
- [c33]Lixiang Li, Yao Chen
MELOPPR: Software/Hardware Co-design for Memory-efficient Low-latency Personalized PageRank. DAC 2021: 601-606 - [c32]Houye Ji, Cheng Yang
Heterogeneous Graph Neural Network with Distance Encoding. ICDM 2021: 1138-1143 - [c31]Eli Chien
Adaptive Universal Generalized PageRank Graph Neural Network. ICLR 2021 - [c30]Yanbang Wang, Yen-Yu Chang, Yunyu Liu, Jure Leskovec, Pan Li:
Inductive Representation Learning in Temporal Networks via Causal Anonymous Walks. ICLR 2021 - [c29]Eli Chien, Pan Li, Olgica Milenkovic:
Landing Probabilities of Random Walks for Seed-Set Expansion in Hypergraphs. ITW 2021: 1-6 - [c28]Susheel Suresh
Breaking the Limit of Graph Neural Networks by Improving the Assortativity of Graphs with Local Mixing Patterns. KDD 2021: 1541-1551 - [c27]Andrew Z. Wang, Rex Ying, Pan Li, Nikhil Rao, Karthik Subbian, Jure Leskovec
Bipartite Dynamic Representations for Abuse Detection. KDD 2021: 3638-3648 - [c26]Muhan Zhang, Pan Li, Yinglong Xia, Kai Wang, Long Jin:
Labeling Trick: A Theory of Using Graph Neural Networks for Multi-Node Representation Learning. NeurIPS 2021: 9061-9073 - [c25]Muhan Zhang, Pan Li:
Nested Graph Neural Networks. NeurIPS 2021: 15734-15747 - [c24]Susheel Suresh, Pan Li, Cong Hao, Jennifer Neville:
Adversarial Graph Augmentation to Improve Graph Contrastive Learning. NeurIPS 2021: 15920-15933 - [c23]Yuhong Li, Cong Hao, Pan Li, Jinjun Xiong, Deming Chen:
Generic Neural Architecture Search via Regression. NeurIPS 2021: 20476-20490 - [c22]Kimon Fountoulakis, Pan Li, Shenghao Yang:
Local Hyper-Flow Diffusion. NeurIPS 2021: 27683-27694 - [c21]Yen-Yu Chang, Pan Li, Rok Sosic, M. H. Afifi, Marco Schweighauser, Jure Leskovec
F-FADE: Frequency Factorization for Anomaly Detection in Edge Streams. WSDM 2021: 589-597 - [c20]Yanbang Wang
TEDIC: Neural Modeling of Behavioral Patterns in Dynamic Social Interaction Networks. WWW 2021: 693-705 - [c19]Meng Liu, Nate Veldt, Haoyu Song, Pan Li, David F. Gleich:
Strongly Local Hypergraph Diffusions for Clustering and Semi-supervised Learning. WWW 2021: 2092-2103 - [c18]Siddharth Bhatia, Arjit Jain, Pan Li, Ritesh Kumar, Bryan Hooi:
MStream: Fast Anomaly Detection in Multi-Aspect Streams. WWW 2021: 3371-3382 - [i33]Yanbang Wang, Yen-Yu Chang, Yunyu Liu, Jure Leskovec, Pan Li:
Inductive Representation Learning in Temporal Networks via Causal Anonymous Walks. CoRR abs/2101.05974 (2021) - [i32]Kimon Fountoulakis, Pan Li, Shenghao Yang:
Local Hyper-flow Diffusion. CoRR abs/2102.07945 (2021) - [i31]Lixiang Li, Yao Chen, Zacharie Zirnheld, Pan Li, Cong Hao:
MELOPPR: Software/Hardware Co-design for Memory-efficient Low-latency Personalized PageRank. CoRR abs/2104.09616 (2021) - [i30]Changlin Wan, Muhan Zhang, Wei Hao, Sha Cao, Pan Li, Chi Zhang:
Principled Hyperedge Prediction with Structural Spectral Features and Neural Networks. CoRR abs/2106.04292 (2021) - [i29]Susheel Suresh, Pan Li, Cong Hao, Jennifer Neville:
Adversarial Graph Augmentation to Improve Graph Contrastive Learning. CoRR abs/2106.05819 (2021) - [i28]Yunyu Liu, Jianzhu Ma, Pan Li:
Neural Higher-order Pattern (Motif) Prediction in Temporal Networks. CoRR abs/2106.06039 (2021) - [i27]Susheel Suresh, Vinith Budde, Jennifer Neville, Pan Li, Jianzhu Ma:
Breaking the Limit of Graph Neural Networks by Improving the Assortativity of Graphs with Local Mixing Patterns. CoRR abs/2106.06586 (2021) - [i26]Hejie Cui, Zijie Lu, Pan Li, Carl Yang:
On Positional and Structural Node Features for Graph Neural Networks on Non-attributed Graphs. CoRR abs/2107.01495 (2021) - [i25]Yuhong Li, Cong Hao, Pan Li, Jinjun Xiong, Deming Chen:
Generic Neural Architecture Search via Regression. CoRR abs/2108.01899 (2021) - [i24]Nan Wu, Huake He, Yuan Xie, Pan Li, Cong Hao:
Program-to-Circuit: Exploiting GNNs for Program Representation and Circuit Translation. CoRR abs/2109.06265 (2021) - [i23]Allison McCarn Deiana, Nhan Tran, Joshua Agar, Michaela Blott, Giuseppe Di Guglielmo, Javier M. Duarte
Applications and Techniques for Fast Machine Learning in Science. CoRR abs/2110.13041 (2021) - [i22]Muhan Zhang, Pan Li:
Nested Graph Neural Networks. CoRR abs/2110.13197 (2021) - 2020
- [j3]Pan Li, Niao He, Olgica Milenkovic:
Quadratic Decomposable Submodular Function Minimization: Theory and Practice. J. Mach. Learn. Res. 21: 106:1-106:49 (2020) - [j2]Pan Li
Motif and Hypergraph Correlation Clustering. IEEE Trans. Inf. Theory 66(5): 3065-3078 (2020) - [c17]Pan Li, Yanbang Wang, Hongwei Wang, Jure Leskovec:
Distance Encoding: Design Provably More Powerful Neural Networks for Graph Representation Learning. NeurIPS 2020 - [c16]Tailin Wu, Hongyu Ren, Pan Li, Jure Leskovec:
Graph Information Bottleneck. NeurIPS 2020 - [i21]Eli Chien, Jianhao Peng, Pan Li, Olgica Milenkovic:
Joint Adaptive Feature Smoothing and Topology Extraction via Generalized PageRank GNNs. CoRR abs/2006.07988 (2020) - [i20]Pan Li, Yanbang Wang, Hongwei Wang, Jure Leskovec:
Distance Encoding - Design Provably More Powerful Graph Neural Networks for Structural Representation Learning. CoRR abs/2009.00142 (2020) - [i19]Siddharth Bhatia, Arjit Jain, Pan Li, Ritesh Kumar, Bryan Hooi:
MStream: Fast Streaming Multi-Aspect Group Anomaly Detection. CoRR abs/2009.08451 (2020) - [i18]Tailin Wu, Hongyu Ren, Pan Li, Jure Leskovec:
Graph Information Bottleneck. CoRR abs/2010.12811 (2020) - [i17]Muhan Zhang, Pan Li, Yinglong Xia, Kai Wang, Long Jin:
Revisiting Graph Neural Networks for Link Prediction. CoRR abs/2010.16103 (2020) - [i16]Yen-Yu Chang, Pan Li, Rok Sosic, M. H. Afifi, Marco Schweighauser, Jure Leskovec:
F-FADE: Frequency Factorization for Anomaly Detection in Edge Streams. CoRR abs/2011.04723 (2020) - [i15]Meng Liu, Nate Veldt, Haoyu Song, Pan Li, David F. Gleich:
Strongly Local Hypergraph Diffusions for Clustering and Semi-supervised Learning. CoRR abs/2011.07752 (2020) - [i14]Haoteng Yin, Yanbang Wang, Pan Li:
Revisit graph neural networks and distance encoding in a practical view. CoRR abs/2011.12228 (2020)
2010 – 2019
- 2019
- [b1]Pan Li:
Learning on graphs with high-order relations: spectral methods, optimization and applications. University of Illinois Urbana-Champaign, USA, 2019 - [c15]I (Eli) Chien, Huozhi Zhou, Pan Li:
HS2: Active learning over hypergraphs with pointwise and pairwise queries. AISTATS 2019: 2466-2475 - [c14]Pan Li, Zhen Qin, Xuanhui Wang, Donald Metzler:
Combining Decision Trees and Neural Networks for Learning-to-Rank in Personal Search. KDD 2019: 2032-2040 - [c13]Carl Yang, Peiye Zhuang, Wenhan Shi, Alan Luu, Pan Li:
Conditional Structure Generation through Graph Variational Generative Adversarial Nets. NeurIPS 2019: 1338-1349 - [c12]Pan Li, I (Eli) Chien, Olgica Milenkovic:
Optimizing Generalized PageRank Methods for Seed-Expansion Community Detection. NeurIPS 2019: 11705-11716 - [i13]Pan Li, Niao He, Olgica Milenkovic:
Quadratic Decomposable Submodular Function Minimization: Theory and Practice. CoRR abs/1902.10132 (2019) - [i12]Pan Li, I (Eli) Chien, Olgica Milenkovic:
Optimizing Generalized PageRank Methods for Seed-Expansion Community Detection. CoRR abs/1905.10881 (2019) - [i11]Carl Yang, Yichen Feng, Pan Li, Yu Shi, Jiawei Han:
Meta-Graph Based HIN Spectral Embedding: Methods, Analyses, and Insights. CoRR abs/1910.00004 (2019) - [i10]Eli Chien, Pan Li, Olgica Milenkovic:
Landing Probabilities of Random Walks for Seed-Set Expansion in Hypergraphs. CoRR abs/1910.09040 (2019) - 2018
- [c11]Carl Yang, Yichen Feng, Pan Li, Yu Shi, Jiawei Han:
Meta-Graph Based HIN Spectral Embedding: Methods, Analyses, and Insights. ICDM 2018: 657-666 - [c10]Pan Li, Olgica Milenkovic:
Submodular Hypergraphs: p-Laplacians, Cheeger Inequalities and Spectral Clustering. ICML 2018: 3020-3029 - [c9]Pan Li, Niao He, Olgica Milenkovic:
Quadratic Decomposable Submodular Function Minimization. NeurIPS 2018: 1062-1072 - [c8]Pan Li, Olgica Milenkovic:
Revisiting Decomposable Submodular Function Minimization with Incidence Relations. NeurIPS 2018: 2242-2252 - [i9]Pan Li, Olgica Milenkovic:
Submodular Hypergraphs: p-Laplacians, Cheeger Inequalities and Spectral Clustering. CoRR abs/1803.03833 (2018) - [i8]Pan Li, Olgica Milenkovic:
Revisiting Decomposable Submodular Function Minimization with Incidence Relations. CoRR abs/1803.03851 (2018) - [i7]Pan Li, Niao He, Olgica Milenkovic:
Quadratic Decomposable Submodular Function Minimization. CoRR abs/1806.09842 (2018) - [i6]Pan Li, Gregory J. Puleo, Olgica Milenkovic:
Motif and Hypergraph Correlation Clustering. CoRR abs/1811.02089 (2018) - [i5]I (Eli) Chien, Huozhi Zhou, Pan Li:
HS2: Active Learning over Hypergraphs. CoRR abs/1811.11549 (2018) - 2017
- [c7]Pan Li, Arya Mazumdar, Olgica Milenkovic:
Efficient Rank Aggregation via Lehmer Codes. AISTATS 2017: 450-459 - [c6]Pan Li, Hoang Dau
Motif clustering and overlapping clustering for social network analysis. INFOCOM 2017: 1-9 - [c5]Pan Li, Olgica Milenkovic:
Multiclass MinMax rank aggregation. ISIT 2017: 3000-3004 - [c4]Pan Li, Olgica Milenkovic:
Inhomogeneous Hypergraph Clustering with Applications. NIPS 2017: 2308-2318 - [i4]Pan Li, Olgica Milenkovic:
Multiclass MinMax Rank Aggregation. CoRR abs/1701.08305 (2017) - [i3]Pan Li, Arya Mazumdar, Olgica Milenkovic:
Efficient Rank Aggregation via Lehmer Codes. CoRR abs/1701.09083 (2017) - [i2]Pan Li, Olgica Milenkovic:
Inhomogeneous Hypergraph Clustering with Applications. CoRR abs/1709.01249 (2017) - 2016
- [j1]Wenbo Ding, Yang Lu, Fang Yang, Wei Dai, Pan Li, Sicong Liu, Jian Song:
Spectrally Efficient CSI Acquisition for Power Line Communications: A Bayesian Compressive Sensing Perspective. IEEE J. Sel. Areas Commun. 34(7): 2022-2032 (2016) - [i1]Pan Li, Son Hoang Dau, Gregory J. Puleo, Olgica Milenkovic:
Motif Clustering and Overlapping Clustering for Social Network Analysis. CoRR abs/1612.00895 (2016) - 2015
- [c3]Pan Li, Wei Dai, Huadong Meng, Xiqin Wang:
On recovery of sparse signals with block structures. ISIT 2015: 546-550 - 2014
- [c2]Pan Li, Huadong Meng, Xiqin Wang:
A Feature Selection Method Based on the Sparse Multi-Class SVM for Fingerprinting Localization. VTC Fall 2014: 1-5 - 2013
- [c1]Chundi Zheng, Gang Li, Pan Li, Xiqin Wang:
Hyperparameter-free DOA estimation under power constraints. ICASSP 2013: 3991-3995
Coauthor Index
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last updated on 2024-12-02 21:29 CET by the dblp team
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