| Inhomogeneous hypergraph clustering with applications P Li, O Milenkovic Advances in Neural Information Processing Systems, 2017 | 115 | 2017 |
| Adaptive universal generalized pagerank graph neural network E Chien, J Peng, P Li, O Milenkovic International Conference on Learning Representations, 2021 | 110 | 2021 |
| Distance encoding: Design provably more powerful neural networks for graph representation learning P Li, Y Wang, H Wang, J Leskovec Advances in Neural Information Processing Systems, 2020 | 81* | 2020 |
| Conditional structure generation through graph variational generative adversarial nets C Yang, P Zhuang, W Shi, A Luu, P Li Advances in Neural Information Processing Systems, 2019 | 62 | 2019 |
| Submodular hypergraphs: p-laplacians, cheeger inequalities and spectral clustering P Li, O Milenkovic International Conference on Machine Learning, 2018 | 60 | 2018 |
| Motif clustering and overlapping clustering for social network analysis P Li, H Dau, G Puleo, O Milenkovic IEEE INFOCOM 2017-IEEE Conference on Computer Communications, 2017 | 52 | 2017 |
| Labeling trick: A theory of using graph neural networks for multi-node representation learning M Zhang, P Li, Y Xia, K Wang, L Jin Advances in Neural Information Processing Systems, 2021 | 47* | 2021 |
| Graph Information Bottleneck T Wu, H Ren, P Li, J Leskovec Advances in Neural Information Processing Systems, 2020 | 47 | 2020 |
| Adversarial Graph Augmentation to Improve Graph Contrastive Learning S Suresh, P Li, C Hao, J Neville Advances in Neural Information Processing Systems, 2021 | 35 | 2021 |
| Spectrally efficient CSI acquisition for power line communications: A Bayesian compressive sensing perspective W Ding, Y Lu, F Yang, W Dai, P Li, S Liu, J Song IEEE Journal on Selected Areas in Communications 34 (7), 2022-2032, 2016 | 35 | 2016 |
| Meta-graph based hin spectral embedding: Methods, analyses, and insights C Yang, Y Feng, P Li, Y Shi, J Han IEEE International Conference on Data Mining, 2018 | 34 | 2018 |
| Optimizing generalized pagerank methods for seed-expansion community detection P Li, E Chien, O Milenkovic Advances in Neural Information Processing Systems, 2019 | 32 | 2019 |
| Inductive Representation Learning in Temporal Networks via Causal Anonymous Walks Y Wang, YY Chang, Y Liu, J Leskovec, P Li International Conference on Learning Representations, 2021 | 29 | 2021 |
| Quadratic Decomposable Submodular Function Minimization: Theory and Practice. P Li, N He, O Milenkovic Journal of Machine Learning Research 21, 106:1-106:49, 2020 | 24* | 2020 |
| Combining decision trees and neural networks for learning-to-rank in personal search P Li, Z Qin, X Wang, D Metzler Proceedings of the ACM SIGKDD International Conference on Knowledge …, 2019 | 20 | 2019 |
| Revisiting decomposable submodular function minimization with incidence relations P Li, O Milenkovic Advances in Neural Information Processing Systems, 2018 | 17 | 2018 |
| Motif and hypergraph correlation clustering P Li, GJ Puleo, O Milenkovic IEEE Transactions on Information Theory 66 (5), 3065-3078, 2019 | 15 | 2019 |
| MSTREAM: Fast anomaly detection in multi-aspect streams S Bhatia, A Jain, P Li, R Kumar, B Hooi Proceedings of the Web Conference, 2021 | 14 | 2021 |
| : Active learning over hypergraphs with pointwise and pairwise queries IE Chien, H Zhou, P Li Artificial Intelligence and Statistics, 2019 | 14 | 2019 |
| F-fade: Frequency factorization for anomaly detection in edge streams YY Chang, P Li, R Sosic, MH Afifi, M Schweighauser, J Leskovec Proceedings of the ACM International Conference on Web Search and Data Mining, 2021 | 13 | 2021 |
Olgica MilenkovicUniversity of IllinoisVerified email at illinois.edu
