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ORCIDJundong Li
Jun-Dong Li
Person information
- affiliation: University of Virginia, Department of Electrical and Computer Engineering, Charlottesville, VA, USA
- affiliation (PhD 2019): Arizona State University, Tempe, AZ, USA
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2020 – today
- 2024
[j41]Ling Jian, Kai Shao, Ying Liu, Jundong Li, Xijun Liang
:
OEC: an online ensemble classifier for mining data streams with noisy labels. Data Min. Knowl. Discov. 38(3): 1101-1124 (2024)- [j40]Song Wang, Chris Tennant, Daniel Moser, Theo Larrieu, Jundong Li:
Graph learning for particle accelerator operations. Frontiers Big Data 7 (2024) - [j39]Qiang Huang, Jing Ma, Jundong Li, Ruocheng Guo, Huiyan Sun, Yi Chang:
Modeling Interference for Individual Treatment Effect Estimation from Networked Observational Data. ACM Trans. Knowl. Discov. Data 18(3): 48:1-48:21 (2024) - [j38]Song Wang, Yushun Dong, Xiao Huang, Chen Chen, Jundong Li:
Learning Hierarchical Task Structures for Few-shot Graph Classification. ACM Trans. Knowl. Discov. Data 18(3): 67:1-67:20 (2024) - [j37]Kaize Ding, Jianling Wang, Jundong Li, James Caverlee, Huan Liu:
Robust Graph Meta-Learning for Weakly Supervised Few-Shot Node Classification. ACM Trans. Knowl. Discov. Data 18(4): 83:1-83:18 (2024) - [j36]Junliang Yu, Hongzhi Yin, Xin Xia, Tong Chen, Jundong Li, Zi Huang:
Self-Supervised Learning for Recommender Systems: A Survey. IEEE Trans. Knowl. Data Eng. 36(1): 335-355 (2024) - [j35]Qiaoyu Tan, Xin Zhang, Xiao Huang, Hao Chen, Jundong Li, Xia Hu:
Collaborative Graph Neural Networks for Attributed Network Embedding. IEEE Trans. Knowl. Data Eng. 36(3): 972-986 (2024) - [c135]Haochen Liu, Song Wang, Yaochen Zhu, Yushun Dong, Jundong Li:
Knowledge Graph-Enhanced Large Language Models via Path Selection. ACL (Findings) 2024: 6311-6321 - [c134]Zihan Chen, Song Wang, Cong Shen, Jundong Li:
FastGAS: Fast Graph-based Annotation Selection for In-Context Learning. ACL (Findings) 2024: 9764-9780 - [c133]Yaochen Zhu, Liang Wu, Binchi Zhang, Song Wang, Qi Guo, Liangjie Hong, Luke Simon, Jundong Li:
Understanding and Modeling Job Marketplace with Pretrained Language Models. CIKM 2024: 5143-5150 - [c132]Zhen Tan, Dawei Li, Song Wang, Alimohammad Beigi, Bohan Jiang, Amrita Bhattacharjee, Mansooreh Karami, Jundong Li, Lu Cheng, Huan Liu:
Large Language Models for Data Annotation and Synthesis: A Survey. EMNLP 2024: 930-957 - [c131]Zhen Tan, Chengshuai Zhao, Raha Moraffah, Yifan Li, Song Wang, Jundong Li, Tianlong Chen, Huan Liu:
Glue pizza and eat rocks - Exploiting Vulnerabilities in Retrieval-Augmented Generative Models. EMNLP 2024: 1610-1626 - [c130]Yinhan He, Zaiyi Zheng, Patrick Soga, Yaochen Zhu, Yushun Dong, Jundong Li:
Explaining Graph Neural Networks with Large Language Models: A Counterfactual Perspective on Molecule Graphs. EMNLP (Findings) 2024: 7079-7096 - [c129]Zihan Chen, Jundong Li, Cong Shen:
Personalized Federated Learning with Attention-Based Client Selection. ICASSP 2024: 6930-6934 - [c128]Binchi Zhang, Yushun Dong, Chen Chen, Yada Zhu, Minnan Luo, Jundong Li:
Adversarial Attacks on Fairness of Graph Neural Networks. ICLR 2024 - [c127]Binchi Zhang, Zihan Chen, Cong Shen, Jundong Li:
Verification of Machine Unlearning is Fragile. ICML 2024 - [c126]Binchi Zhang, Yushun Dong, Tianhao Wang, Jundong Li:
Towards Certified Unlearning for Deep Neural Networks. ICML 2024 - [c125]Yushun Dong, Binchi Zhang, Zhenyu Lei, Na Zou, Jundong Li:
IDEA: A Flexible Framework of Certified Unlearning for Graph Neural Networks. KDD 2024: 621-630 - [c124]Xingbo Fu, Zihan Chen, Binchi Zhang, Chen Chen, Jundong Li:
Federated Graph Learning with Structure Proxy Alignment. KDD 2024: 827-838 - [c123]Yaochen Zhu, Yinhan He, Jing Ma, Mengxuan Hu, Sheng Li, Jundong Li:
Causal Inference with Latent Variables: Recent Advances and Future Prospectives. KDD 2024: 6677-6687 - [c122]Chuxu Zhang, Dongkuan Xu, Kaize Ding, Jundong Li, Mojan Javaheripi, Subhabrata Mukherjee, Nitesh V. Chawla, Huan Liu:
RelKD 2024: The Second International Workshop on Resource-Efficient Learning for Knowledge Discovery. KDD 2024: 6749-6750 - [c121]Chen Zhao, Feng Chen, Xintao Wu, Jundong Li, Haifeng Chen:
3rd Workshop on Ethical Artificial Intelligence: Methods and Applications (EAI). KDD 2024: 6751-6752 - [c120]Haochen Liu, Song Wang, Chen Chen, Jundong Li:
Few-shot Knowledge Graph Relational Reasoning via Subgraph Adaptation. NAACL-HLT 2024: 3346-3356 - [c119]Zhen Tan, Lu Cheng, Song Wang, Bo Yuan, Jundong Li, Huan Liu:
Interpreting Pretrained Language Models via Concept Bottlenecks. PAKDD (3) 2024: 56-74 - [c118]Xianren Zhang, Jing Ma, Yushun Dong, Chen Chen, Min Gao, Jundong Li:
SD-Attack: Targeted Spectral Attacks on Graphs. PAKDD (2) 2024: 352-363 - [c117]Yushun Dong, Zhenyu Lei, Zaiyi Zheng, Song Wang, Jing Ma, Alex Jing Huang, Chen Chen, Jundong Li:
PyGDebias: A Python Library for Debiasing in Graph Learning. WWW (Companion Volume) 2024: 1019-1022 - [c116]Yaochen Zhu, Liang Wu, Qi Guo, Liangjie Hong, Jundong Li:
Collaborative Large Language Model for Recommender Systems. WWW 2024: 3162-3172 - [i99]Zhen Tan, Alimohammad Beigi, Song Wang, Ruocheng Guo, Amrita Bhattacharjee, Bohan Jiang, Mansooreh Karami, Jundong Li, Lu Cheng, Huan Liu:
Large Language Models for Data Annotation: A Survey. CoRR abs/2402.13446 (2024) - [i98]Song Wang, Zhen Tan, Xinyu Zhao, Tianlong Chen, Huan Liu, Jundong Li:
GraphRCG: Self-conditioned Graph Generation via Bootstrapped Representations. CoRR abs/2403.01071 (2024) - [i97]Xuansheng Wu, Haiyan Zhao, Yaochen Zhu, Yucheng Shi, Fan Yang, Tianming Liu, Xiaoming Zhai, Wenlin Yao, Jundong Li, Mengnan Du, Ninghao Liu:
Usable XAI: 10 Strategies Towards Exploiting Explainability in the LLM Era. CoRR abs/2403.08946 (2024) - [i96]Song Wang, Yushun Dong, Binchi Zhang, Zihan Chen, Xingbo Fu, Yinhan He, Cong Shen, Chuxu Zhang, Nitesh V. Chawla, Jundong Li:
Safety in Graph Machine Learning: Threats and Safeguards. CoRR abs/2405.11034 (2024) - [i95]Mucong Ding, Yinhan He, Jundong Li, Furong Huang:
Spectral Greedy Coresets for Graph Neural Networks. CoRR abs/2405.17404 (2024) - [i94]Zihan Chen, Song Wang, Cong Shen, Jundong Li:
FastGAS: Fast Graph-based Annotation Selection for In-Context Learning. CoRR abs/2406.03730 (2024) - [i93]Alexi Gladstone, Ganesh Nanduru, Md Mofijul Islam, Aman Chadha, Jundong Li, Tariq Iqbal:
Cognitively Inspired Energy-Based World Models. CoRR abs/2406.08862 (2024) - [i92]Haochen Liu, Song Wang, Yaochen Zhu, Yushun Dong, Jundong Li:
Knowledge Graph-Enhanced Large Language Models via Path Selection. CoRR abs/2406.13862 (2024) - [i91]Yaochen Zhu, Yinhan He, Jing Ma, Mengxuan Hu, Sheng Li, Jundong Li:
Causal Inference with Latent Variables: Recent Advances and Future Prospectives. CoRR abs/2406.13966 (2024) - [i90]Haochen Liu, Song Wang, Chen Chen, Jundong Li:
Few-shot Knowledge Graph Relational Reasoning via Subgraph Adaptation. CoRR abs/2406.15507 (2024) - [i89]Zhen Tan, Chengshuai Zhao, Raha Moraffah, Yifan Li, Song Wang, Jundong Li, Tianlong Chen, Huan Liu:
"Glue pizza and eat rocks" - Exploiting Vulnerabilities in Retrieval-Augmented Generative Models. CoRR abs/2406.19417 (2024) - [i88]Song Wang, Peng Wang, Tong Zhou, Yushun Dong, Zhen Tan, Jundong Li:
CEB: Compositional Evaluation Benchmark for Fairness in Large Language Models. CoRR abs/2407.02408 (2024) - [i87]Yushun Dong, Song Wang, Zhenyu Lei, Zaiyi Zheng, Jing Ma, Chen Chen, Jundong Li:
A Benchmark for Fairness-Aware Graph Learning. CoRR abs/2407.12112 (2024) - [i86]Yushun Dong, Binchi Zhang, Zhenyu Lei, Na Zou, Jundong Li:
IDEA: A Flexible Framework of Certified Unlearning for Graph Neural Networks. CoRR abs/2407.19398 (2024) - [i85]Binchi Zhang, Yushun Dong, Tianhao Wang, Jundong Li:
Towards Certified Unlearning for Deep Neural Networks. CoRR abs/2408.00920 (2024) - [i84]Binchi Zhang, Zihan Chen, Cong Shen, Jundong Li:
Verification of Machine Unlearning is Fragile. CoRR abs/2408.00929 (2024) - [i83]Yaochen Zhu, Liang Wu, Binchi Zhang, Song Wang, Qi Guo, Liangjie Hong, Luke Simon, Jundong Li:
Understanding and Modeling Job Marketplace with Pretrained Language Models. CoRR abs/2408.04381 (2024) - [i82]Xingbo Fu, Zihan Chen, Binchi Zhang, Chen Chen, Jundong Li:
Federated Graph Learning with Structure Proxy Alignment. CoRR abs/2408.09393 (2024) - [i81]Zihan Chen, Bike Xie, Jundong Li, Cong Shen:
Channel-Wise Mixed-Precision Quantization for Large Language Models. CoRR abs/2410.13056 (2024) - [i80]Yinhan He, Zaiyi Zheng, Patrick Soga, Yaozhen Zhu, Yushun Dong, Jundong Li:
Explaining Graph Neural Networks with Large Language Models: A Counterfactual Perspective for Molecular Property Prediction. CoRR abs/2410.15165 (2024) - [i79]Kexin Zhang, Shuhan Liu, Song Wang, Weili Shi, Chen Chen, Pan Li, Sheng Li, Jundong Li, Kaize Ding:
A Survey of Deep Graph Learning under Distribution Shifts: from Graph Out-of-Distribution Generalization to Adaptation. CoRR abs/2410.19265 (2024) - [i78]Yinhan He, Wendy Zheng, Yaochen Zhu, Jing Ma, Saumitra Mishra, Natraj Raman, Ninghao Liu, Jundong Li:
Global Graph Counterfactual Explanation: A Subgraph Mapping Approach. CoRR abs/2410.19978 (2024) - 2023
- [j34]Jing Ma, Mengting Wan, Longqi Yang, Jundong Li, Brent J. Hecht, Jaime Teevan:
Causal Effect Estimation under Interference on Hypergraphs. AI Matters 9(2): 15-19 (2023) - [j33]Jing Luo, Jundong Li, Qi Mao, Zhenghao Shi, Haiqin Liu, Xiaoyong Ren, Xinhong Hei:
Overlapping filter bank convolutional neural network for multisubject multicategory motor imagery brain-computer interface. BioData Min. 16(1) (2023) - [j32]Zhen Peng, Minnan Luo, Wenbing Huang, Jundong Li, Qinghua Zheng, Fuchun Sun, Junzhou Huang:
Learning Representations by Graphical Mutual Information Estimation and Maximization. IEEE Trans. Pattern Anal. Mach. Intell. 45(1): 722-737 (2023) - [j31]Han Yue, Jundong Li, Hongfu Liu:
Second-Order Unsupervised Feature Selection via Knowledge Contrastive Distillation. IEEE Trans. Pattern Anal. Mach. Intell. 45(12): 15577-15587 (2023) - [j30]Xiaotian Han, Kaixiong Zhou, Ting-Hsiang Wang, Jundong Li, Fei Wang, Na Zou:
Marginal Nodes Matter: Towards Structure Fairness in Graphs. SIGKDD Explor. 25(2): 4-13 (2023) - [j29]Yushun Dong, Jing Ma, Song Wang, Chen Chen, Jundong Li:
Fairness in Graph Mining: A Survey. IEEE Trans. Knowl. Data Eng. 35(10): 10583-10602 (2023) - [j28]Chunhui Zhang, Hongfu Liu, Jundong Li, Yanfang Ye, Chuxu Zhang:
Mind the Gap: Mitigating the Distribution Gap in Graph Few-shot Learning. Trans. Mach. Learn. Res. 2023 (2023) - [c115]Yushun Dong, Song Wang, Jing Ma, Ninghao Liu, Jundong Li:
Interpreting Unfairness in Graph Neural Networks via Training Node Attribution. AAAI 2023: 7441-7449 - [c114]Zhenyu Lei, Herun Wan, Wenqian Zhang, Shangbin Feng, Zilong Chen, Jundong Li, Qinghua Zheng, Minnan Luo:
BIC: Twitter Bot Detection with Text-Graph Interaction and Semantic Consistency. ACL (1) 2023: 10326-10340 - [c113]Song Wang, Jundong Li:
Generative Few-shot Graph Classification: An Adaptive Perspective. ACSSC 2023: 317-321 - [c112]Yucheng Shi, Yushun Dong, Qiaoyu Tan, Jundong Li, Ninghao Liu:
GiGaMAE: Generalizable Graph Masked Autoencoder via Collaborative Latent Space Reconstruction. CIKM 2023: 2259-2269 - [c111]Song Wang, Jing Ma, Lu Cheng, Jundong Li:
Fair Few-Shot Learning with Auxiliary Sets. ECAI 2023: 2517-2524 - [c110]Song Wang, Zhen Tan, Ruocheng Guo, Jundong Li:
Noise-Robust Fine-Tuning of Pretrained Language Models via External Guidance. EMNLP (Findings) 2023: 12528-12540 - [c109]Zhen Peng, Minnan Luo, Jundong Li, Luguo Xue, Qinghua Zheng:
A Deep Multi-View Framework for Anomaly Detection on Attributed Networks (Extended Abstract). ICDE 2023: 3799-3800 - [c108]Xingbo Fu, Chen Chen, Yushun Dong, Anil Vullikanti, Eili Klein, Gregory Madden, Jundong Li:
Spatial-Temporal Networks for Antibiogram Pattern Prediction. ICHI 2023: 225-234 - [c107]Jing Ma, Mengting Wan, Longqi Yang, Jundong Li, Brent J. Hecht, Jaime Teevan:
Learning Causal Effects on Hypergraphs (Extended Abstract). IJCAI 2023: 6463-6467 - [c106]Jing Ma, Ruocheng Guo, Aidong Zhang, Jundong Li:
Learning for Counterfactual Fairness from Observational Data. KDD 2023: 1620-1630 - [c105]Jihong Wang, Minnan Luo, Jundong Li, Yun Lin, Yushun Dong, Jin Song Dong, Qinghua Zheng:
Empower Post-hoc Graph Explanations with Information Bottleneck: A Pre-training and Fine-tuning Perspective. KDD 2023: 2349-2360 - [c104]Song Wang, Xingbo Fu, Kaize Ding, Chen Chen, Huiyuan Chen, Jundong Li:
Federated Few-shot Learning. KDD 2023: 2374-2385 - [c103]Song Wang, Zhen Tan, Huan Liu, Jundong Li:
Contrastive Meta-Learning for Few-shot Node Classification. KDD 2023: 2386-2397 - [c102]Yaochen Zhu, Jing Ma, Liang Wu, Qi Guo, Liangjie Hong, Jundong Li:
Path-Specific Counterfactual Fairness for Recommender Systems. KDD 2023: 3638-3649 - [c101]Jing Ma, Chen Chen, Anil Vullikanti, Ritwick Mishra, Gregory Madden, Daniel Borrajo, Jundong Li:
A Look into Causal Effects under Entangled Treatment in Graphs: Investigating the Impact of Contact on MRSA Infection. KDD 2023: 4584-4594 - [c100]Yushun Dong, Oyku Deniz Kose, Yanning Shen, Jundong Li:
Fairness in Graph Machine Learning: Recent Advances and Future Prospectives. KDD 2023: 5794-5795 - [c99]Chuxu Zhang, Dongkuan Xu, Mojan Javaheripi, Subhabrata Mukherjee, Lingfei Wu, Yinglong Xia, Jundong Li, Meng Jiang, Yanzhi Wang:
RelKD 2023: International Workshop on Resource-Efficient Learning for Knowledge Discovery. KDD 2023: 5901-5902 - [c98]Yushun Dong, Binchi Zhang, Yiling Yuan, Na Zou, Qi Wang, Jundong Li:
RELIANT: Fair Knowledge Distillation for Graph Neural Networks. SDM 2023: 154-162 - [c97]Yushun Dong, Jundong Li, Tobias Schnabel:
When Newer is Not Better: Does Deep Learning Really Benefit Recommendation From Implicit Feedback? SIGIR 2023: 942-952 - [c96]Song Wang, Yushun Dong, Kaize Ding, Chen Chen, Jundong Li:
Few-shot Node Classification with Extremely Weak Supervision. WSDM 2023: 276-284 - [c95]Zhaoxuan Tan, Zilong Chen, Shangbin Feng, Qingyue Zhang, Qinghua Zheng, Jundong Li, Minnan Luo:
KRACL: Contrastive Learning with Graph Context Modeling for Sparse Knowledge Graph Completion. WWW 2023: 2548-2559 - [i77]Yaochen Zhu, Jing Ma, Jundong Li:
Causal Inference in Recommender Systems: A Survey of Strategies for Bias Mitigation, Explanation, and Generalization. CoRR abs/2301.00910 (2023) - [i76]Yushun Dong, Binchi Zhang, Yiling Yuan, Na Zou, Qi Wang, Jundong Li:
RELIANT: Fair Knowledge Distillation for Graph Neural Networks. CoRR abs/2301.01150 (2023) - [i75]Song Wang, Yushun Dong, Kaize Ding, Chen Chen, Jundong Li:
Few-shot Node Classification with Extremely Weak Supervision. CoRR abs/2301.02708 (2023) - [i74]Xingbo Fu, Chen Chen, Yushun Dong, Anil Vullikanti, Eili Klein, Gregory Madden, Jundong Li:
Spatial-Temporal Networks for Antibiogram Pattern Prediction. CoRR abs/2305.01761 (2023) - [i73]Yushun Dong, Jundong Li, Tobias Schnabel:
When Newer is Not Better: Does Deep Learning Really Benefit Recommendation From Implicit Feedback? CoRR abs/2305.01801 (2023) - [i72]Yaochen Zhu, Jing Ma, Liang Wu, Qi Guo, Liangjie Hong, Jundong Li:
Path-Specific Counterfactual Fairness for Recommender Systems. CoRR abs/2306.02615 (2023) - [i71]Song Wang, Xingbo Fu, Kaize Ding, Chen Chen, Huiyuan Chen, Jundong Li:
Federated Few-shot Learning. CoRR abs/2306.10234 (2023) - [i70]Song Wang, Zhen Tan, Huan Liu, Jundong Li:
Contrastive Meta-Learning for Few-shot Node Classification. CoRR abs/2306.15154 (2023) - [i69]Jing Ma, Ruocheng Guo, Aidong Zhang, Jundong Li:
Learning for Counterfactual Fairness from Observational Data. CoRR abs/2307.08232 (2023) - [i68]Jing Ma, Chen Chen, Anil Vullikanti, Ritwick Mishra, Gregory Madden, Daniel Borrajo, Jundong Li:
A Look into Causal Effects under Entangled Treatment in Graphs: Investigating the Impact of Contact on MRSA Infection. CoRR abs/2307.08237 (2023) - [i67]Qiaoyu Tan, Xin Zhang, Xiao Huang, Hao Chen, Jundong Li, Xia Hu:
Collaborative Graph Neural Networks for Attributed Network Embedding. CoRR abs/2307.11981 (2023) - [i66]Yucheng Shi, Yushun Dong, Qiaoyu Tan, Jundong Li, Ninghao Liu:
GiGaMAE: Generalizable Graph Masked Autoencoder via Collaborative Latent Space Reconstruction. CoRR abs/2308.09663 (2023) - [i65]Song Wang, Jing Ma, Lu Cheng, Jundong Li:
Fair Few-shot Learning with Auxiliary Sets. CoRR abs/2308.14338 (2023) - [i64]Binchi Zhang, Yushun Dong, Chen Chen, Yada Zhu, Minnan Luo, Jundong Li:
Adversarial Attacks on Fairness of Graph Neural Networks. CoRR abs/2310.13822 (2023) - [i63]Xiaotian Han, Kaixiong Zhou, Ting-Hsiang Wang, Jundong Li, Fei Wang, Na Zou:
Marginal Nodes Matter: Towards Structure Fairness in Graphs. CoRR abs/2310.14527 (2023) - [i62]Mouxiang Chen, Zemin Liu, Chenghao Liu, Jundong Li, Qiheng Mao, Jianling Sun:
ULTRA-DP: Unifying Graph Pre-training with Multi-task Graph Dual Prompt. CoRR abs/2310.14845 (2023) - [i61]Song Wang, Yaochen Zhu, Haochen Liu, Zaiyi Zheng, Chen Chen, Jundong Li:
Knowledge Editing for Large Language Models: A Survey. CoRR abs/2310.16218 (2023) - [i60]Song Wang, Zhen Tan, Ruocheng Guo, Jundong Li:
Noise-Robust Fine-Tuning of Pretrained Language Models via External Guidance. CoRR abs/2311.01108 (2023) - [i59]Yaochen Zhu, Liang Wu, Qi Guo, Liangjie Hong, Jundong Li:
Collaborative Large Language Model for Recommender Systems. CoRR abs/2311.01343 (2023) - [i58]Yushun Dong, Binchi Zhang, Hanghang Tong, Jundong Li:
ELEGANT: Certified Defense on the Fairness of Graph Neural Networks. CoRR abs/2311.02757 (2023) - [i57]Zhen Tan, Lu Cheng, Song Wang, Yuan Bo, Jundong Li, Huan Liu:
Interpreting Pretrained Language Models via Concept Bottlenecks. CoRR abs/2311.05014 (2023) - [i56]Zihan Chen, Jundong Li, Cong Shen:
Personalized Federated Learning with Attention-based Client Selection. CoRR abs/2312.15148 (2023) - 2022
- [j27]Jing Ma, Jundong Li:
Learning Causality with Graphs. AI Mag. 43(4): 365-375 (2022) - [j26]Lei Cai, Jundong Li, Jie Wang, Shuiwang Ji:
Line Graph Neural Networks for Link Prediction. IEEE Trans. Pattern Anal. Mach. Intell. 44(9): 5103-5113 (2022) - [j25]Xingbo Fu, Binchi Zhang, Yushun Dong, Chen Chen, Jundong Li:
Federated Graph Machine Learning: A Survey of Concepts, Techniques, and Applications. SIGKDD Explor. 24(2): 32-47 (2022) - [j24]Zongwei Wang, Min Gao, Jundong Li, Junwei Zhang, Jiang Zhong:
Gray-Box Shilling Attack: An Adversarial Learning Approach. ACM Trans. Intell. Syst. Technol. 13(5): 82:1-82:21 (2022) - [j23]Yixiang Dong, Minnan Luo, Jundong Li, Deng Cai, Qinghua Zheng:
LookCom: Learning Optimal Network for Community Detection. IEEE Trans. Knowl. Data Eng. 34(2): 764-775 (2022) - [j22]Zhen Peng, Minnan Luo, Jundong Li, Luguo Xue, Qinghua Zheng:
A Deep Multi-View Framework for Anomaly Detection on Attributed Networks. IEEE Trans. Knowl. Data Eng. 34(6): 2539-2552 (2022) - [j21]Junliang Yu, Hongzhi Yin, Jundong Li, Min Gao, Zi Huang, Lizhen Cui:
Enhancing Social Recommendation With Adversarial Graph Convolutional Networks. IEEE Trans. Knowl. Data Eng. 34(8): 3727-3739 (2022) - [j20]Kaize Ding, Kai Shu, Xuan Shan, Jundong Li, Huan Liu:
Cross-Domain Graph Anomaly Detection. IEEE Trans. Neural Networks Learn. Syst. 33(6): 2406-2415 (2022) - [c94]Song Wang, Yushun Dong, Xiao Huang, Chen Chen, Jundong Li:
FAITH: Few-Shot Graph Classification with Hierarchical Task Graphs. IJCAI 2022: 2284-2290 - [c93]Chuxu Zhang, Kaize Ding, Jundong Li, Xiangliang Zhang, Yanfang Ye, Nitesh V. Chawla, Huan Liu:
Few-Shot Learning on Graphs. IJCAI 2022: 5662-5669 - [c92]Yushun Dong, Song Wang, Yu Wang, Tyler Derr, Jundong Li:
On Structural Explanation of Bias in Graph Neural Networks. KDD 2022: 316-326 - [c91]Jing Ma