Ninghao Liu

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Xia "Ben" HuAssociate Professor of Computer Science, Rice UniversityAdresă de e-mail confirmată pe rice.edu
Mengnan DuAssistant Professor, New Jersey Institute of TechnologyAdresă de e-mail confirmată pe njit.edu
Tianming LiuDistinguished Research Professor of Computer Science, University of GeorgiaAdresă de e-mail confirmată pe cs.uga.edu
Fan YangAssistant Professor of Computer Science, Wake Forest UniversityAdresă de e-mail confirmată pe wfu.edu
Qiaoyu (Smach) TanAssistant Professor of Computer Science, New York University (Shanghai)Adresă de e-mail confirmată pe nyu.edu
Xuansheng WuUniversity of GeorgiaAdresă de e-mail confirmată pe uga.edu
Xiao HuangAssistant Professor at The Hong Kong Polytechnic UniversityAdresă de e-mail confirmată pe comp.polyu.edu.hk
Xiang LiAssistant Professor, Massachusetts General Hospital and Harvard Medical SchoolAdresă de e-mail confirmată pe mgh.harvard.edu
Jundong LiAssistant Professor, University of VirginiaAdresă de e-mail confirmată pe virginia.edu
Yucheng ShiUniversity of GeorgiaAdresă de e-mail confirmată pe uga.edu
Rui ChenChief Scientist, Samsung Ads / Senior Director of Engineering (AI), Samsung Research AmericaAdresă de e-mail confirmată pe samsung.com
Kaixiong ZhouMIT, NCSUAdresă de e-mail confirmată pe ncsu.edu
Xiaoming ZhaiUniversity of GeorgiaAdresă de e-mail confirmată pe uga.edu
Xiaotian (Max) HanCase Western Reserve UniversityAdresă de e-mail confirmată pe case.edu
James CaverleeProfessor, Computer Science and Engineering, Texas A&M UniversityAdresă de e-mail confirmată pe cse.tamu.edu
Qingquan SongLinkedIn
Hongxia YangProfessor, HK Polytechnic University

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Ninghao Liu

Assistant Professor, University of Georgia

Adresă de e-mail confirmată pe uga.edu - Pagina de pornire

Explainable AI Fairness in Machine Learning Graph Mining Anomaly Detection


Titlu Sortați după descrierea bibliografică Sortați după an Sortați după titlu	Citat de Citat de	Anul
Techniques for interpretable machine learning M Du, N Liu, X Hu Communications of the ACM 63 (1), 68-77, 2019	1466	2019
Explainability for large language models: A survey H Zhao, H Chen, F Yang, N Liu, H Deng, H Cai, S Wang, D Yin, M Du ACM Transactions on Intelligent Systems and Technology 15 (2), 1-38, 2024	330	2024
Auggpt: Leveraging chatgpt for text data augmentation H Dai, Z Liu, W Liao, X Huang, Y Cao, Z Wu, L Zhao, S Xu, W Liu, N Liu, ... arXiv preprint arXiv:2302.13007, 2023	312*	2023
G-mixup: Graph data augmentation for graph classification X Han, Z Jiang, N Liu, X Hu International Conference on Machine Learning, 8230-8248, 2022	207	2022
An embarrassingly simple approach for trojan attack in deep neural networks R Tang, M Du, N Liu, F Yang, X Hu Proceedings of the 26th ACM SIGKDD international conference on knowledge …, 2020	195	2020
Towards explanation of dnn-based prediction with guided feature inversion M Du, N Liu, Q Song, X Hu Proceedings of the 24th ACM SIGKDD International Conference on Knowledge …, 2018	159	2018
On the Opportunities and Challenges of Foundation Models for GeoAI (Vision Paper) G Mai, W Huang, J Sun, S Song, D Mishra, N Liu, S Gao, T Liu, G Cong, ... ACM Transactions on Spatial Algorithms and Systems, 2024	152*	2024
Sparse-interest network for sequential recommendation Q Tan, J Zhang, J Yao, N Liu, J Zhou, H Yang, X Hu Proceedings of the 14th ACM international conference on web search and data …, 2021	147	2021
Edits: Modeling and mitigating data bias for graph neural networks Y Dong, N Liu, B Jalaian, J Li Proceedings of the ACM web conference 2022, 1259-1269, 2022	137	2022
Deep representation learning for social network analysis Q Tan, N Liu, X Hu Frontiers in big Data 2, 2, 2019	133	2019
In-processing modeling techniques for machine learning fairness: A survey M Wan, D Zha, N Liu, N Zou ACM Transactions on Knowledge Discovery from Data 17 (3), 1-27, 2023	124	2023
S2GAE: self-supervised graph autoencoders are generalizable learners with graph masking Q Tan, N Liu, X Huang, SH Choi, L Li, R Chen, X Hu Proceedings of the sixteenth ACM international conference on web search and …, 2023	118*	2023
Artificial general intelligence (AGI) for education E Latif, G Mai, M Nyaaba, X Wu, N Liu, G Lu, S Li, T Liu, X Zhai arXiv preprint arXiv:2304.12479, 2023	106*	2023
Learning to hash with graph neural networks for recommender systems Q Tan, N Liu, X Zhao, H Yang, J Zhou, X Hu Proceedings of The Web Conference 2020, 1988-1998, 2020	106	2020
Is a single vector enough? exploring node polysemy for network embedding N Liu, Q Tan, Y Li, H Yang, J Zhou, X Hu Proceedings of the 25th ACM SIGKDD International Conference on Knowledge …, 2019	102	2019
Contextual outlier interpretation N Liu, D Shin, X Hu Proceedings of the 27th International Joint Conference on Artificial …, 2018	100	2018
Adversarial detection with model interpretation N Liu, H Yang, X Hu Proceedings of the 24th ACM SIGKDD International Conference on Knowledge …, 2018	83	2018
Dynamic memory based attention network for sequential recommendation Q Tan, J Zhang, N Liu, X Huang, H Yang, J Zhou, X Hu Proceedings of the AAAI conference on artificial intelligence 35 (5), 4384-4392, 2021	74	2021
Accelerated Local Anomaly Detection via Resolving Attributed Networks. N Liu, X Huang, X Hu IJCAI, 2337-2343, 2017	71	2017
On interpretation of network embedding via taxonomy induction N Liu, X Huang, J Li, X Hu Proceedings of the 24th ACM SIGKDD International Conference on Knowledge …, 2018	67	2018

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