default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
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
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2025
[j42]Song Wang
, Yaochen Zhu, Haochen Liu, Zaiyi Zheng, Chen Chen, Jundong Li:
Knowledge Editing for Large Language Models: A Survey. ACM Comput. Surv. 57(3): 59:1-59:37 (2025)- 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, Mengting Wan, Longqi Yang, Jundong Li, Brent J. Hecht, Jaime Teevan:
Learning Causal Effects on Hypergraphs. KDD 2022: 1202-1212 - [c90]Weihao Song, Yushun Dong, Ninghao Liu, Jundong Li:
GUIDE: Group Equality Informed Individual Fairness in Graph Neural Networks. KDD 2022: 1625-1634 - [c89]Song Wang, Kaize Ding, Chuxu Zhang, Chen Chen, Jundong Li:
Task-Adaptive Few-shot Node Classification. KDD 2022: 1910-1919 - [c88]Yu Wang, Yuying Zhao, Yushun Dong, Huiyuan Chen, Jundong Li, Tyler Derr:
Improving Fairness in Graph Neural Networks via Mitigating Sensitive Attribute Leakage. KDD 2022: 1938-1948 - [c87]Guansong Pang, Jundong Li, Anton van den Hengel, Longbing Cao, Thomas G. Dietterich:
ANDEA: Anomaly and Novelty Detection, Explanation, and Accommodation. KDD 2022: 4892-4893 - [c86]Zhen Tan, Song Wang, Kaize Ding, Jundong Li, Huan Liu:
Transductive Linear Probing: A Novel Framework for Few-Shot Node Classification. LoG 2022: 4 - [c85]Wenqian Zhang, Shangbin Feng, Zilong Chen, Zhenyu Lei, Jundong Li, Minnan Luo:
KCD: Knowledge Walks and Textual Cues Enhanced Political Perspective Detection in News Media. NAACL-HLT 2022: 4129-4140 - [c84]Shangbin Feng, Zhaoxuan Tan, Herun Wan, Ningnan Wang, Zilong Chen, Binchi Zhang, Qinghua Zheng, Wenqian Zhang, Zhenyu Lei, Shujie Yang, Xinshun Feng, Qingyue Zhang, Hongrui Wang, Yuhan Liu, Yuyang Bai, Heng Wang, Zijian Cai, Yanbo Wang, Lijing Zheng, Zihan Ma, Jundong Li, Minnan Luo:
TwiBot-22: Towards Graph-Based Twitter Bot Detection. NeurIPS 2022 - [c83]Kay Liu, Yingtong Dou, Yue Zhao, Xueying Ding, Xiyang Hu, Ruitong Zhang, Kaize Ding, Canyu Chen, Hao Peng, Kai Shu, Lichao Sun, Jundong Li, George H. Chen, Zhihao Jia, Philip S. Yu:
BOND: Benchmarking Unsupervised Outlier Node Detection on Static Attributed Graphs. NeurIPS 2022 - [c82]Jing Ma, Ruocheng Guo, Saumitra Mishra, Aidong Zhang, Jundong Li:
CLEAR: Generative Counterfactual Explanations on Graphs. NeurIPS 2022 - [c81]Song Wang, Chen Chen, Jundong Li:
Graph Few-shot Learning with Task-specific Structures. NeurIPS 2022 - [c80]Zhiming Xu, Xiao Huang, Yue Zhao, Yushun Dong, Jundong Li:
Contrastive Attributed Network Anomaly Detection with Data Augmentation. PAKDD (2) 2022: 444-457 - [c79]Qiang Huang, Jing Ma, Jundong Li, Huiyan Sun, Yi Chang:
SemiITE: Semi-supervised Individual Treatment Effect Estimation via Disagreement-Based Co-training. ECML/PKDD (4) 2022: 400-417 - [c78]Zheng Huang, Jing Ma, Yushun Dong, Natasha Zhang Foutz, Jundong Li:
Empowering Next POI Recommendation with Multi-Relational Modeling. SIGIR 2022: 2034-2038 - [c77]Jing Ma, Ruocheng Guo, Mengting Wan, Longqi Yang, Aidong Zhang, Jundong Li:
Learning Fair Node Representations with Graph Counterfactual Fairness. WSDM 2022: 695-703 - [c76]Kaize Ding, Jundong Li, Nitesh V. Chawla, Huan Liu:
Graph Minimally-supervised Learning. WSDM 2022: 1620-1622 - [c75]Xiaotian Han, Zhimeng Jiang, Ninghao Liu, Qingquan Song, Jundong Li, Xia Hu:
Geometric Graph Representation Learning via Maximizing Rate Reduction. WWW 2022: 1226-1237 - [c74]Yushun Dong, Ninghao Liu, Brian Jalaian, Jundong Li:
EDITS: Modeling and Mitigating Data Bias for Graph Neural Networks. WWW 2022: 1259-1269 - [c73]Nan Wang, Lu Lin, Jundong Li, Hongning Wang:
Unbiased Graph Embedding with Biased Graph Observations. WWW 2022: 1423-1433 - [c72]Jing Ma, Yushun Dong, Zheng Huang, Daniel Mietchen, Jundong Li:
Assessing the Causal Impact of COVID-19 Related Policies on Outbreak Dynamics: A Case Study in the US. WWW 2022: 2678-2686 - [i55]Jing Ma, Ruocheng Guo, Mengting Wan, Longqi Yang, Aidong Zhang, Jundong Li:
Learning Fair Node Representations with Graph Counterfactual Fairness. CoRR abs/2201.03662 (2022) - [i54]Jihong Wang, Minnan Luo, Jundong Li, Ziqi Liu, Jun Zhou, Qinghua Zheng:
Robust Unsupervised Graph Representation Learning via Mutual Information Maximization. CoRR abs/2201.08557 (2022) - [i53]Xiaotian Han, Zhimeng Jiang, Ninghao Liu, Qingquan Song, Jundong Li, Xia Hu:
Geometric Graph Representation Learning via Maximizing Rate Reduction. CoRR abs/2202.06241 (2022) - [i52]Chuxu Zhang, Kaize Ding, Jundong Li, Xiangliang Zhang, Yanfang Ye, Nitesh V. Chawla, Huan Liu:
Few-Shot Learning on Graphs: A Survey. CoRR abs/2203.09308 (2022) - [i51]Junliang Yu, Hongzhi Yin, Xin Xia, Tong Chen, Jundong Li, Zi Huang:
Self-Supervised Learning for Recommender Systems: A Survey. CoRR abs/2203.15876 (2022) - [i50]Wenqian Zhang, Shangbin Feng, Zilong Chen, Zhenyu Lei, Jundong Li, Minnan Luo:
KCD: Knowledge Walks and Textual Cues Enhanced Political Perspective Detection in News Media. CoRR abs/2204.04046 (2022) - [i49]Yushun Dong, Jing Ma, Chen Chen, Jundong Li:
Fairness in Graph Mining: A Survey. CoRR abs/2204.09888 (2022) - [i48]Zheng Huang, Jing Ma, Yushun Dong, Natasha Zhang Foutz, Jundong Li:
Empowering Next POI Recommendation with Multi-Relational Modeling. CoRR abs/2204.12288 (2022) - [i47]Song Wang, Yushun Dong, Xiao Huang, Chen Chen, Jundong Li:
FAITH: Few-Shot Graph Classification with Hierarchical Task Graphs. CoRR abs/2205.02435 (2022) - [i46]Qinghua Zheng, Jihong Wang, Minnan Luo, Yaoliang Yu, Jundong Li, Lina Yao, Xiaojun Chang:
Towards Explanation for Unsupervised Graph-Level Representation Learning. CoRR abs/2205.09934 (2022) - [i45]Yu Wang, Yuying Zhao, Yushun Dong, Huiyuan Chen, Jundong Li, Tyler Derr:
Improving Fairness in Graph Neural Networks via Mitigating Sensitive Attribute Leakage. CoRR abs/2206.03426 (2022) - [i44]Shangbin Feng, Zhaoxuan Tan, Herun Wan, Ningnan Wang, Zilong Chen, Binchi Zhang, Qinghua Zheng, Wenqian Zhang, Zhenyu Lei, Shujie Yang, Xinshun Feng, Qingyue Zhang, Hongrui Wang, Yuhan Liu, Yuyang Bai, Heng Wang, Zijian Cai, Yanbo Wang, Lijing Zheng, Zihan Ma, Jundong Li, Minnan Luo:
TwiBot-22: Towards Graph-Based Twitter Bot Detection. CoRR abs/2206.04564 (2022) - [i43]Kay Liu, Yingtong Dou, Yue Zhao, Xueying Ding, Xiyang Hu, Ruitong Zhang, Kaize Ding, Canyu Chen, Hao Peng, Kai Shu, Lichao Sun, Jundong Li, George H. Chen, Zhihao Jia, Philip S. Yu:
Benchmarking Node Outlier Detection on Graphs. CoRR abs/2206.10071 (2022) - [i42]Song Wang, Kaize Ding, Chuxu Zhang, Chen Chen, Jundong Li:
Task-Adaptive Few-shot Node Classification. CoRR abs/2206.11972 (2022) - [i41]Yushun Dong, Song Wang, Yu Wang, Tyler Derr, Jundong Li:
On Structural Explanation of Bias in Graph Neural Networks. CoRR abs/2206.12104 (2022) - [i40]Jing Ma, Mengting Wan, Longqi Yang, Jundong Li, Brent J. Hecht, Jaime Teevan:
Learning Causal Effects on Hypergraphs. CoRR abs/2207.04049 (2022) - [i39]Xingbo Fu, Binchi Zhang, Yushun Dong, Chen Chen, Jundong Li:
Federated Graph Machine Learning: A Survey of Concepts, Techniques, and Applications. CoRR abs/2207.11812 (2022) - [i38]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. CoRR abs/2208.07622 (2022) - [i37]Chunhui Zhang, Hongfu Liu, Jundong Li, Yanfang Ye, Chuxu Zhang:
Contrastive Graph Few-Shot Learning. CoRR abs/2210.00084 (2022) - [i36]Jing Ma, Ruocheng Guo, Saumitra Mishra, Aidong Zhang, Jundong Li:
CLEAR: Generative Counterfactual Explanations on Graphs. CoRR abs/2210.08443 (2022) - [i35]Song Wang, Chen Chen, Jundong Li:
Graph Few-shot Learning with Task-specific Structures. CoRR abs/2210.12130 (2022) - [i34]Yushun Dong, Song Wang, Jing Ma, Ninghao Liu, Jundong Li:
Interpreting Unfairness in Graph Neural Networks via Training Node Attribution. CoRR abs/2211.14383 (2022) - [i33]Zhen Tan, Song Wang, Kaize Ding, Jundong Li, Huan Liu:
Transductive Linear Probing: A Novel Framework for Few-Shot Node Classification. CoRR abs/2212.05606 (2022) - 2021
- [j19]Ruocheng Guo, Lu Cheng, Jundong Li, P. Richard Hahn, Huan Liu:
A Survey of Learning Causality with Data: Problems and Methods. ACM Comput. Surv. 53(4): 75:1-75:37 (2021) - [j18]Xijun Liang, Xiaoxin Song, Kai Qi, Jundong Li, Jinyu Liu, Ling Jian:
Anomaly Detection Aided Budget Online Classification for Imbalanced Data Streams. IEEE Intell. Syst. 36(3): 14-22 (2021) - [j17]Min Gao, Junwei Zhang, Junliang Yu, Jundong Li, Junhao Wen, Qingyu Xiong:
Recommender systems based on generative adversarial networks: A problem-driven perspective. Inf. Sci. 546: 1166-1185 (2021) - [j16]Kefei Tu, Chen Chen, Chunyan Hou, Jing Yuan, Jundong Li, Xiaojie Yuan:
Rumor2vec: A rumor detection framework with joint text and propagation structure representation learning. Inf. Sci. 560: 137-151 (2021) - [j15]Chen Chen, Yinglong Xia, Hui Zang, Jundong Li, Huan Liu, Hanghang Tong:
Incremental one-class collaborative filtering with co-evolving side networks. Knowl. Inf. Syst. 63(1): 105-124 (2021) - [c71]Yushun Dong, Kaize Ding, Brian Jalaian, Shuiwang Ji, Jundong Li:
AdaGNN: Graph Neural Networks with Adaptive Frequency Response Filter. CIKM 2021: 392-401 - [c70]Song Wang, Xiao Huang, Chen Chen, Liang Wu, Jundong Li:
REFORM: Error-Aware Few-Shot Knowledge Graph Completion. CIKM 2021: 1979-1988 - [c69]Junwei Zhang, Min Gao, Junliang Yu, Lei Guo, Jundong Li, Hongzhi Yin:
Double-Scale Self-Supervised Hypergraph Learning for Group Recommendation. CIKM 2021: 2557-2567 - [c68]Xiaoying Xing, Hongfu Liu, Chen Chen, Jundong Li:
Fairness-Aware Unsupervised Feature Selection. CIKM 2021: 3548-3552 - [c67]Shangbin Feng, Herun Wan, Ningnan Wang, Jundong Li, Minnan Luo:
SATAR: A Self-supervised Approach to Twitter Account Representation Learning and its Application in Bot Detection. CIKM 2021: 3808-3817 - [c66]Shangbin Feng, Herun Wan, Ningnan Wang, Jundong Li, Minnan Luo:
TwiBot-20: A Comprehensive Twitter Bot Detection Benchmark. CIKM 2021: 4485-4494 - [c65]Jing Ma, Ruocheng Guo, Aidong Zhang, Jundong Li:
Multi-Cause Effect Estimation with Disentangled Confounder Representation. IJCAI 2021: 2790-2796 - [c64]Yitong Li, Duoduo Liao, Jundong Li, Wenying Ji:
Automated Generation of Disaster Response Networks through Information Extraction. ISCRAM 2021: 431-438 - [c63]Yushun Dong, Jian Kang, Hanghang Tong, Jundong Li:
Individual Fairness for Graph Neural Networks: A Ranking based Approach. KDD 2021: 300-310 - [c62]Ji Gao, Xiao Huang, Jundong Li:
Unsupervised Graph Alignment with Wasserstein Distance Discriminator. KDD 2021: 426-435 - [c61]Chuxu Zhang, Jundong Li, Meng Jiang:
Data Efficient Learning on Graphs. KDD 2021: 4092-4093 - [c60]Guansong Pang, Jundong Li, Anton van den Hengel, Longbing Cao, Thomas G. Dietterich:
Anomaly and Novelty Detection, Explanation, and Accommodation (ANDEA). KDD 2021: 4145-4146 - [c59]Jing Ma, Ruocheng Guo, Chen Chen, Aidong Zhang, Jundong Li:
Deconfounding with Networked Observational Data in a Dynamic Environment. WSDM 2021: 166-174 - [c58]Liang Wu, Mihajlo Grbovic, Jundong Li:
Toward User Engagement Optimization in 2D Presentation. WSDM 2021: 1047-1055 - [c57]Junliang Yu, Hongzhi Yin, Jundong Li, Qinyong Wang, Nguyen Quoc Viet Hung, Xiangliang Zhang:
Self-Supervised Multi-Channel Hypergraph Convolutional Network for Social Recommendation. WWW 2021: 413-424 - [i32]Junliang Yu, Hongzhi Yin, Jundong Li, Qinyong Wang, Nguyen Quoc Viet Hung, Xiangliang Zhang:
Self-Supervised Multi-Channel Hypergraph Convolutional Network for Social Recommendation. CoRR abs/2101.06448 (2021) - [i31]Yitong Li, Duoduo Liao, Jundong Li, Wenying Ji:
Automated Generation of Interorganizational Disaster Response Networks through Information Extraction. CoRR abs/2103.00287 (2021) - [i30]Yushun Dong, Kaize Ding, Brian Jalaian, Shuiwang Ji, Jundong Li:
Graph Neural Networks with Adaptive Frequency Response Filter. CoRR abs/2104.12840 (2021) - [i29]Jing Ma, Yushun Dong, Zheng Huang, Daniel Mietchen, Jundong Li:
Assessing the Causal Impact of COVID-19 Related Policies on Outbreak Dynamics: A Case Study in the US. CoRR abs/2106.01315 (2021) - [i28]Xiaoying Xing, Hongfu Liu, Chen Chen, Jundong Li:
Fairness-Aware Unsupervised Feature Selection. CoRR abs/2106.02216 (2021) - [i27]Kaize Ding, Jianling Wang, Jundong Li, James Caverlee, Huan Liu:
Weakly-supervised Graph Meta-learning for Few-shot Node Classification. CoRR abs/2106.06873 (2021) - [i26]Shangbin Feng, Herun Wan, Ningnan Wang, Jundong Li, Minnan Luo:
TwiBot-20: A Comprehensive Twitter Bot Detection Benchmark. CoRR abs/2106.13088 (2021) - [i25]Shangbin Feng, Herun Wan, Ningnan Wang, Jundong Li, Minnan Luo:
SATAR: A Self-supervised Approach to Twitter Account Representation Learning and its Application in Bot Detection. CoRR abs/2106.13089 (2021) - [i24]Yushun Dong, Ninghao Liu, Brian Jalaian, Jundong Li:
EDITS: Modeling and Mitigating Data Bias for Graph Neural Networks. CoRR abs/2108.05233 (2021) - [i23]Junwei Zhang, Min Gao, Junliang Yu, Lei Guo, Jundong Li, Hongzhi Yin:
Double-Scale Self-Supervised Hypergraph Learning for Group Recommendation. CoRR abs/2109.04200 (2021) - [i22]Nan Wang, Lu Lin, Jundong Li, Hongning Wang:
Unbiased Graph Embedding with Biased Graph Observations. CoRR abs/2110.13957 (2021) - 2020
- [j14]Jihong Wang, Minnan Luo, Fnu Suya, Jundong Li, Zijiang Yang, Qinghua Zheng:
Scalable attack on graph data by injecting vicious nodes. Data Min. Knowl. Discov. 34(5): 1363-1389 (2020) - [j13]Mingyang Lu, Zhenjiang Fan, Bin Xu, Lujun Chen, Xiao Zheng, Jundong Li, Taieb Znati, Qi Mi, Jingting Jiang:
Using machine learning to predict ovarian cancer. Int. J. Medical Informatics 141: 104195 (2020) - [j12]Zhongping Lin, Minnan Luo, Zhen Peng, Jundong Li, Qinghua Zheng:
Nonlinear feature selection on attributed networks. Neurocomputing 410: 161-173 (2020) - [j11]Yuxin Ma, Tiankai Xie, Jundong Li, Ross Maciejewski:
Explaining Vulnerabilities to Adversarial Machine Learning through Visual Analytics. IEEE Trans. Vis. Comput. Graph. 26(1): 1075-1085 (2020) - [c56]Lu Cheng, Jundong Li, K. Selçuk Candan, Huan Liu:
Tracking Disaster Footprints with Social Streaming Data. AAAI 2020: 370-377 - [c55]Yan Zhong, Xiao Huang, Jundong Li, Xia Hu:
Scalable Social Tie Strength Measuring. ASONAM 2020: 288-295 - [c54]Kaize Ding, Jianling Wang, Jundong Li, Kai Shu, Chenghao Liu, Huan Liu:
Graph Prototypical Networks for Few-shot Learning on Attributed Networks. CIKM 2020: 295-304 - [c53]Ning Wang, Minnan Luo, Kaize Ding, Lingling Zhang, Jundong Li, Qinghua Zheng:
Graph Few-shot Learning with Attribute Matching. CIKM 2020: 1545-1554 - [c52]Yuzhe Zhang, Chen Chen, Minnan Luo, Jundong Li, Caixia Yan, Qinghua Zheng:
Unsupervised Hierarchical Feature Selection on Networked Data. DASFAA (3) 2020: 137-153 - [c51]Kaize Ding, Jianling Wang, Jundong Li, Dingcheng Li, Huan Liu:
Be More with Less: Hypergraph Attention Networks for Inductive Text Classification. EMNLP (1) 2020: 4927-4936 - [c50]Kaize Ding, Jundong Li, Nitin Agarwal, Huan Liu:
Inductive Anomaly Detection on Attributed Networks. IJCAI 2020: 1288-1294 - [c49]Ruocheng Guo, Jundong Li, Yichuan Li, K. Selçuk Candan, Adrienne Raglin, Huan Liu:
IGNITE: A Minimax Game Toward Learning Individual Treatment Effects from Networked Observational Data. IJCAI 2020: 4534-4540 - [c48]Ruocheng Guo, Jundong Li, Huan Liu:
Counterfactual Evaluation of Treatment Assignment Functions with Networked Observational Data. SDM 2020: 271-279 - [c47]Ruocheng Guo, Jundong Li, Huan Liu:
Learning Individual Causal Effects from Networked Observational Data. WSDM 2020: 232-240 - [i21]Min Gao, Junwei Zhang, Junliang Yu, Jundong Li, Junhao Wen, Qingyu Xiong:
Recommender Systems Based on Generative Adversarial Networks: A Problem-Driven Perspective. CoRR abs/2003.02474 (2020) - [i20]Junliang Yu, Hongzhi Yin, Jundong Li, Min Gao, Zi Huang, Lizhen Cui:
Enhance Social Recommendation with Adversarial Graph Convolutional Networks. CoRR abs/2004.02340 (2020) - [i19]Jihong Wang, Minnan Luo, Fnu Suya, Jundong Li, Zijiang Yang, Qinghua Zheng:
Scalable Attack on Graph Data by Injecting Vicious Nodes. CoRR abs/2004.13825 (2020) - [i18]Kaize Ding, Jianling Wang, Jundong Li, Kai Shu, Chenghao Liu, Huan Liu:
Graph Prototypical Networks for Few-shot Learning on Attributed Networks. CoRR abs/2006.12739 (2020) - [i17]Lei Cai, Jundong Li, Jie Wang, Shuiwang Ji:
Line Graph Neural Networks for Link Prediction. CoRR abs/2010.10046 (2020) - [i16]Kaize Ding, Jianling Wang, Jundong Li, Dingcheng Li, Huan Liu:
Be More with Less: Hypergraph Attention Networks for Inductive Text Classification. CoRR abs/2011.00387 (2020)
2010 – 2019
- 2019
- [b1]Jundong Li:
Learning with Attributed Networks: Algorithms and Applications. Arizona State University, Tempe, USA, 2019 - [j10]Xuying Meng, Suhang Wang, Kai Shu, Jundong Li, Bo Chen, Huan Liu, Yujun Zhang:
Towards privacy preserving social recommendation under personalized privacy settings. World Wide Web 22(6): 2853-2881 (2019) - [c46]Jundong Li, Liang Wu, Ruocheng Guo, Chenghao Liu, Huan Liu:
Multi-level network embedding with boosted low-rank matrix approximation. ASONAM 2019: 49-56 - [c45]Yuening Li, Xiao Huang, Jundong Li, Mengnan Du, Na Zou:
SpecAE: Spectral AutoEncoder for Anomaly Detection in Attributed Networks. CIKM 2019: 2233-2236 - [c44]Luguo Xue, Minnan Luo, Zhen Peng, Jundong Li, Yan Chen, Jun Liu:
Anomaly Detection in Time-Evolving Attributed Networks. DASFAA (3) 2019: 235-239 - [c43]Jianwen Yin, Chenghao Liu, Jundong Li, Bing Tian Dai, Yun-chen Chen, Min Wu, Jianling Sun:
Online Collaborative Filtering with Implicit Feedback. DASFAA (2) 2019: 433-448 - [c42]Zhen Peng, Minnan Luo, Jundong Li, Chen Chen, Qinghua Zheng:
Heterogeneous Information Network Hashing for Fast Nearest Neighbor Search. DASFAA (1) 2019: 571-586 - [c41]Junliang Yu, Min Gao, Hongzhi Yin, Jundong Li, Chongming Gao, Qinyong Wang:
Generating Reliable Friends via Adversarial Training to Improve Social Recommendation. ICDM 2019: 768-777 - [c40]Lu Cheng, Jundong Li, Yasin N. Silva, Deborah L. Hall, Huan Liu:
PI-Bully: Personalized Cyberbullying Detection with Peer Influence. IJCAI 2019: 5829-5835 - [c39]Kaize Ding, Jundong Li, Shivam Dhar, Shreyash Devan, Huan Liu:
InterSpot: Interactive Spammer Detection in Social Media. IJCAI 2019: 6509-6511 - [c38]Yuening Li, Ninghao Liu, Jundong Li, Mengnan Du, Xia Hu:
Deep Structured Cross-Modal Anomaly Detection. IJCNN 2019: 1-8 - [c37]Jundong Li, Ruocheng Guo, Chenghao Liu, Huan Liu:
Adaptive Unsupervised Feature Selection on Attributed Networks. KDD 2019: 92-100 - [c36]Xiao Huang, Peng Cui, Yuxiao Dong, Jundong Li, Huan Liu, Jian Pei, Le Song, Jie Tang, Fei Wang, Hongxia Yang, Wenwu Zhu:
Learning From Networks: Algorithms, Theory, and Applications. KDD 2019: 3221-3222 - [c35]Kaize Ding, Jundong Li, Rohit Bhanushali, Huan Liu:
Deep Anomaly Detection on Attributed Networks. SDM 2019: 594-602 - [c34]Chenghao Liu, Teng Zhang, Jundong Li, Jianwen Yin, Peilin Zhao, Jianling Sun, Steven C. H. Hoi:
Robust Factorization Machine: A Doubly Capped Norms Minimization. SDM 2019: 738-746 - [c33]Lu Cheng, Jundong Li, Yasin N. Silva, Deborah L. Hall, Huan Liu:
XBully: Cyberbullying Detection within a Multi-Modal Context. WSDM 2019: 339-347 - [c32]Kaize Ding, Jundong Li, Huan Liu:
Interactive Anomaly Detection on Attributed Networks. WSDM 2019: 357-365 - [i15]Ruocheng Guo, Jundong Li, Huan Liu:
Learning Individual Treatment Effects from Networked Observational Data. CoRR abs/1906.03485 (2019) - [i14]Yuxin Ma, Tiankai Xie, Jundong Li, Ross Maciejewski:
Explaining Vulnerabilities to Adversarial Machine Learning through Visual Analytics. CoRR abs/1907.07296 (2019) - [i13]Yuening Li, Ninghao Liu, Jundong Li, Mengnan Du, Xia Hu:
Deep Structured Cross-Modal Anomaly Detection. CoRR abs/1908.03848 (2019) - [i12]Yuening Li, Xiao Huang, Jundong Li, Mengnan Du, Na Zou:
SpecAE: Spectral AutoEncoder for Anomaly Detection in Attributed Networks. CoRR abs/1908.03849 (2019) - [i11]Kaize Ding, Yichuan Li, Jundong Li, Chenghao Liu, Huan Liu:
Graph Neural Networks with High-order Feature Interactions. CoRR abs/1908.07110 (2019) - [i10]Junliang Yu, Min Gao, Hongzhi Yin, Jundong Li, Chongming Gao, Qinyong Wang:
Generating Reliable Friends via Adversarial Training to Improve Social Recommendation. CoRR abs/1909.03529 (2019) - [i9]Ruocheng Guo, Jundong Li, Huan Liu:
Counterfactual Evaluation of Treatment Assignment Functions with Networked Observational Data. CoRR abs/1912.10536 (2019) - 2018
- [j9]Jundong Li, Kewei Cheng, Suhang Wang, Fred Morstatter, Robert P. Trevino, Jiliang Tang, Huan Liu:
Feature Selection: A Data Perspective. ACM Comput. Surv. 50(6): 94:1-94:45 (2018) - [j8]Ling Jian, Jundong Li, Huan Liu:
Toward online node classification on streaming networks. Data Min. Knowl. Discov. 32(1): 231-257 (2018) - [j7]Ling Jian, Jundong Li, Huan Liu:
Exploiting Multilabel Information for Noise-Resilient Feature Selection. ACM Trans. Intell. Syst. Technol. 9(5): 52:1-52:23 (2018) - [j6]Xiao Huang, Jundong Li, Na Zou, Xia Hu:
A General Embedding Framework for Heterogeneous Information Learning in Large-Scale Networks. ACM Trans. Knowl. Discov. Data 12(6): 70:1-70:24 (2018) - [c31]Jundong Li, Liang Wu, Harsh Dani, Huan Liu:
Unsupervised Personalized Feature Selection. AAAI 2018: 3514-3521 - [c30]Xuying Meng, Suhang Wang, Kai Shu, Jundong Li, Bo Chen, Huan Liu, Yujun Zhang:
Personalized Privacy-Preserving Social Recommendation. AAAI 2018: 3796-3803 - [c29]Junliang Yu, Min Gao, Jundong Li, Hongzhi Yin, Huan Liu:
Adaptive Implicit Friends Identification over Heterogeneous Network for Social Recommendation. CIKM 2018: 357-366 - [c28]Shan-Yun Teng, Jundong Li, Lo Pang-Yun Ting, Kun-Ta Chuang, Huan Liu:
Interactive Unknowns Recommendation in E-Learning Systems. ICDM 2018: 497-506 - [c27]Ruocheng Guo, Jundong Li, Huan Liu:
INITIATOR: Noise-contrastive Estimation for Marked Temporal Point Process. IJCAI 2018: 2191-2197 - [c26]Zhen Peng, Minnan Luo, Jundong Li, Huan Liu, Qinghua Zheng:
ANOMALOUS: A Joint Modeling Approach for Anomaly Detection on Attributed Networks. IJCAI 2018: 3513-3519 - [c25]Ninghao Liu, Xiao Huang, Jundong Li, Xia Hu:
On Interpretation of Network Embedding via Taxonomy Induction. KDD 2018: 1812-1820 - [c24]Jundong Li, Chen Chen, Hanghang Tong, Huan Liu:
Multi-Layered Network Embedding. SDM 2018: 684-692 - [c23]Liang Wu, Jundong Li, Fred Morstatter, Huan Liu:
Toward Relational Learning with Misinformation. SDM 2018: 711-719 - [c22]Xiao Huang, Qingquan Song, Jundong Li, Xia Hu:
Exploring Expert Cognition for Attributed Network Embedding. WSDM 2018: 270-278 - [c21]Jundong Li, Kewei Cheng, Liang Wu, Huan Liu:
Streaming Link Prediction on Dynamic Attributed Networks. WSDM 2018: 369-377 - [c20]Jundong Li, Jiliang Tang, Yilin Wang, Yali Wan, Yi Chang, Huan Liu:
Understanding and Predicting Delay in Reciprocal Relations. WWW 2018: 1643-1652 - [i8]Jundong Li, Liang Wu, Huan Liu:
Multi-Level Network Embedding with Boosted Low-Rank Matrix Approximation. CoRR abs/1808.08627 (2018) - [i7]Ruocheng Guo, Lu Cheng, Jundong Li, P. Richard Hahn, Huan Liu:
A Survey of Learning Causality with Data: Problems and Methods. CoRR abs/1809.09337 (2018) - [i6]Binbin Liu, Jundong Li, Yunquan Song, Xijun Liang, Ling Jian, Huan Liu:
Online Newton Step Algorithm with Estimated Gradient. CoRR abs/1811.09955 (2018) - 2017
- [j5]Jundong Li, Huan Liu:
Challenges of Feature Selection for Big Data Analytics. IEEE Intell. Syst. 32(2): 9-15 (2017) - [j4]Jundong Li, Osmar R. Zaïane:
Exploiting statistically significant dependent rules for associative classification. Intell. Data Anal. 21(5): 1155-1172 (2017) - [j3]Ling Jian, Jundong Li, Shihua Luo:
Exploiting Expertise Rules for Statistical Data-Driven Modeling. IEEE Trans. Ind. Electron. 64(11): 8647-8656 (2017) - [j2]Ling Jian, Shuqian Shen, Jundong Li, Xijun Liang, Lei Li:
Budget Online Learning Algorithm for Least Squares SVM. IEEE Trans. Neural Networks Learn. Syst. 28(9): 2076-2087 (2017) - [c19]Kewei Cheng, Jundong Li, Jiliang Tang, Huan Liu:
Unsupervised Sentiment Analysis with Signed Social Networks. AAAI 2017: 3429-3435 - [c18]Jundong Li, Harsh Dani, Xia Hu, Jiliang Tang, Yi Chang, Huan Liu:
Attributed Network Embedding for Learning in a Dynamic Environment. CIKM 2017: 387-396 - [c17]Jundong Li, Harsh Dani, Xia Hu, Huan Liu:
Radar: Residual Analysis for Anomaly Detection in Attributed Networks. IJCAI 2017: 2152-2158 - [c16]Jundong Li, Jiliang Tang, Huan Liu:
Reconstruction-based Unsupervised Feature Selection: An Embedded Approach. IJCAI 2017: 2159-2165 - [c15]Kewei Cheng, Jundong Li, Huan Liu:
Unsupervised Feature Selection in Signed Social Networks. KDD 2017: 777-786 - [c14]Harsh Dani, Jundong Li, Huan Liu:
Sentiment Informed Cyberbullying Detection in Social Media. ECML/PKDD (1) 2017: 52-67 - [c13]Liang Wu, Jundong Li, Xia Hu, Huan Liu:
Gleaning Wisdom from the Past: Early Detection of Emerging Rumors in Social Media. SDM 2017: 99-107 - [c12]Jundong Li, Liang Wu, Osmar R. Zaïane, Huan Liu:
Toward Personalized Relational Learning. SDM 2017: 444-452 - [c11]Xiao Huang, Jundong Li, Xia Hu:
Accelerated Attributed Network Embedding. SDM 2017: 633-641 - [c10]Xiao Huang, Jundong Li, Xia Hu:
Label Informed Attributed Network Embedding. WSDM 2017: 731-739 - [c9]Yilin Wang, Jiliang Tang, Jundong Li, Baoxin Li, Yali Wan, Clayton Mellina, Neil O'Hare, Yi Chang:
Understanding and Discovering Deliberate Self-harm Content in Social Media. WWW 2017: 93-102 - [i5]Jundong Li, Jiliang Tang, Yilin Wang, Yali Wan, Yi Chang, Huan Liu:
Understanding and Predicting Delay in Reciprocal Relations. CoRR abs/1703.01393 (2017) - [i4]Jundong Li, Harsh Dani, Xia Hu, Jiliang Tang, Yi Chang, Huan Liu:
Attributed Network Embedding for Learning in a Dynamic Environment. CoRR abs/1706.01860 (2017) - 2016
- [j1]Jundong Li, Aibek Adilmagambetov, Mohomed Shazan Mohomed Jabbar, Osmar R. Zaïane, Alvaro Osornio-Vargas, Osnat Wine:
On discovering co-location patterns in datasets: a case study of pollutants and child cancers. GeoInformatica 20(4): 651-692 (2016) - [c8]Kewei Cheng, Jundong Li, Huan Liu:
FeatureMiner: A Tool for Interactive Feature Selection. CIKM 2016: 2445-2448 - [c7]Jundong Li, Xia Hu, Ling Jian, Huan Liu:
Toward Time-Evolving Feature Selection on Dynamic Networks. ICDM 2016: 1003-1008 - [c6]Ling Jian, Jundong Li, Kai Shu, Huan Liu:
Multi-Label Informed Feature Selection. IJCAI 2016: 1627-1633 - [c5]Jundong Li, Xia Hu, Liang Wu, Huan Liu:
Robust Unsupervised Feature Selection on Networked Data. SDM 2016: 387-395 - [i3]Jundong Li, Kewei Cheng, Suhang Wang, Fred Morstatter, Robert P. Trevino, Jiliang Tang, Huan Liu:
Feature Selection: A Data Perspective. CoRR abs/1601.07996 (2016) - [i2]Jundong Li, Huan Liu:
Challenges of Feature Selection for Big Data Analytics. CoRR abs/1611.01875 (2016) - 2015
- [c4]Jundong Li, Osmar R. Zaïane:
Associative Classification with Statistically Significant Positive and Negative Rules. CIKM 2015: 633-642 - [c3]Jundong Li, Xia Hu, Jiliang Tang, Huan Liu:
Unsupervised Streaming Feature Selection in Social Media. CIKM 2015: 1041-1050 - 2014
- [c2]Jundong Li, Jörg Sander, Ricardo J. G. B. Campello, Arthur Zimek:
Active Learning Strategies for Semi-Supervised DBSCAN. Canadian AI 2014: 179-190 - [c1]Jundong Li, Osmar R. Zaïane, Alvaro Osornio-Vargas:
Discovering Statistically Significant Co-location Rules in Datasets with Extended Spatial Objects. DaWaK 2014: 124-135 - [p1]Luiza Antonie, Jundong Li, Osmar R. Zaïane:
Negative Association Rules. Frequent Pattern Mining 2014: 135-145 - [i1]Jundong Li, Aibek Adilmagambetov, Osmar R. Zaïane, Alvaro Osornio-Vargas, Osnat Wine:
On Discovering Co-Location Patterns in Datasets: A Case Study of Pollutants and Child Cancers. CoRR abs/1412.7282 (2014)
Coauthor Index
[j38] [c135] [c130] [c128] [c126] [c125] [c118] [c117] [i96] [i92] [i88] [i87] [i86] [i85] [i80] [j29] [c115] [c112] [c108] [c105] [c100] [c98] [c97] [c96] [i76] [i75] [i74] [i73] [i66] [i64] [i58] [j25] [c94] [c92] [c90] [c88] [c80] [c78] [c74] [c72] [i49] [i48] [i47] [i45] [i41] [i39] [i34] [c71] [c63] [i30] [i29] [i24]
[j37] [c132] [c131] [c122] [c119] [i99] [i98] [i89] [c103] [i70] [i57] [j20] [c93] [c86] [c76] [i52] [i33] [j19] [j15] [i27] [c56] [c54] [c51] [c50] [c49] [c48] [c47] [i18] [i16] [j10] [c46] [c40] [c39] [c37] [c36] [c35] [c33] [c32] [i15] [i11] [i9] [j9] [j8] [j7] [c31] [c30] [c29] [c28] [c27] [c26] [c24] [c23] [c21] [c20] [i8] [i7] [i6] [j5] [c19] [c18] [c17] [c16] [c15] [c14] [c13] [c12] [i5] [i4] [c8] [c7] [c6] [c5] [i3] [i2] [c3]
[j42] [j40] [j38] [c135] [c134] [c133] [c132] [c131] [c120] [c119] [c117] [i99] [i98] [i96] [i94] [i92] [i90] [i89] [i88] [i87] [i83] [i79] [j29] [c115] [c113] [c111] [c110] [c104] [c103] [c96] [i75] [i71] [i70] [i65] [i61] [i60] [i57] [c94] [c92] [c89] [c86] [c81] [i47] [i42] [i41] [i35] [i34] [i33] [c70]
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-12-23 19:33 CET by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
