[Publications] [Honors] [Professional Service] [Teaching] [Students] [中文简历]
I am an associate professor in the College of Computer Science and Technology at Nanjing University of Aeronautics and Astronautics. I received my B.Sc. and Ph.D. degrees in computer science from Nanjing University in 2010 and 2018, respectively, under the supervision of Prof. Yuan Jiang and Prof. Zhi-Hua Zhou. I was a member ofLAMDA Group from 2010 to 2018, and visited University of Birmingham in 2014 for 3 months and University of Notre Dame in 2015.11-2016.11 for one year. My research interests include machine learning and data mining. Specifically I am working on crowdsourcing, multi-label learning, noisy label learning.
News:
- 2023-09 第十八届“挑战杯”专项赛全国特等奖
- 2023-06 郑宇祥、赵世佶 CVPR2023 持续学习竞赛第4名
- 2022-08 宗辰辰、曹正涛、郭洪涛、杜云、谢明昆 IJCAI-ECAI 2022第一届噪声标记学习挖掘挑战赛
- 2021-08-20 万文海、王蕾、陈佳瑶 win the Third Prize of Preliminary Winners In the 2nd Contest of Promoting BRICS Cooperation in Industrial Innovation and the 2021 International Challenge on Ocean Targets Intelligent Perception [Ann]
- 2019-09 Got foundation from National Science Foundation (No.61906089)
- 2019-07 Got foundation from Jiangsu Province Basic Research Program (No.BK20190408)
Publications [Journal Article] [Conference Paper] [Others]
Journal Article
-
UNM: A Universal Approach for Noisy Multi-label Learning.
Jia-Yao Chen, Shao-Yuan Li*, Sheng-Jun Huang, Songcan Chen, Ming-Kun Xie.
IEEE Transactions on Knowledge and Data Engineering(TKDE), 2024. -
Robust Domain Adaptation with Noisy and Shifted Label Distribution.
Shao-Yuan Li*, Shi-Ji Zhao, Zheng-Tao Cao, Sheng-Jun Huang, Songcan Chen.
Frontiers of Computer Science (FCS), 2024. -
KD-Crowd: A Knowledge Distillation Framework for Learning from Crowds.
Shao-Yuan Li*, Yu-Xiang Zheng, Ye Shi, Sheng-Jun Huang, Songcan Chen.
Frontiers of Computer Science (FCS), 2024. -
Learning from Crowds with Sparse and Imbalanced Annotations.
Ye Shi, Shao-Yuan Li*, Sheng-Jun Huang.
Machine Learning (MLJ), 2023, 112: 1823-1845. - Improving Deep Label Noise Learning with Dual Active Label Correction.
Shao-Yuan Li*, Ye Shi, Sheng-Jun Huang and Songcan Chen
In: Machine Learning (ML), 2022, 111: 1103-1124. - Deep Generative Crowdsourcing Learning with Worker Correlation Utilization.
Shao-Yuan Li *, Meng-Long Wei and Sheng-Jun Huang
In: Ruan Jian Xue Bao/Journal of Software (JOS), 2022, 33(4): 1274-1286. - Crowdsourcing Aggregation with Deep Bayesian
Learning .
Shao-Yuan Li *, Sheng-Jun Huang and Songcan Chen
In: Science China Information Science (SCIS), 64:3, 2021.[pdf] [code] - Incremental Multi-Label Learning with Active Queries.
Sheng-Jun Huang, Guo-Xiang Li, Wen-Yu Huang and Shao-Yuan Li
In: Journal of Computer Science and Technology (JCST), 35(2):234-246, 2020.[pdf] - Multi-Label Crowdsourcing Learning..
Shao-Yuan Li and Yuan Jiang
In: Ruan Jian Xue Bao/Journal of Software (JOS),31(5):1497-1510, 2020. - Multi-Label Learning from Crowds.
Shao-Yuan Li , Yuan Jiang, Nitesh V. Chawla and Zhi-Hua Zhou
In: IEEE Transactions on Knowledge and Data Engineering (TKDE), 31(7): 1369-1382, 2019.[pdf] [code]
- Unlocking the Power of Open Set: A New Perspective for Open-set Noisy Label Learning.
Wenhai Wan, Xinrui Wang, Ming-Kun Xie, Shao-Yuan Li*, Sheng-Jun Huang, Songcan Chen
In: Proceedings of the 38th AAAI Conference on Artificial Intelligence (AAAI'24), 2024. - Beyond Myopia: Learning from Positive and Unlabeled Data through Holistic Predictive Trends.
Xinrui Wang, Wenhai Wan, Chuanxing Geng, Shao-Yuan Li*, Songcan Chen*
In: Proceedings of the Thirty-seventh Annual Conference on Neural Information Processing Systems (NeurIPS'23), 2023. -
Personalized Federated Semi-Supervised Learning with Black-Box Models.
Siyin Huang, Shao-Yuan Li, Songcan Chen
In: Proceedings of 2023 IEEE International Conference on Data Mining (ICDM'23), 2023. - Uncertainty Aware Graph Gaussian Process for Semi-Supervised Learning.
Zhao-Yang Liu, Shao-Yuan Li, Songcan Chen, Yao Hu and Sheng-Jun Huang
In: Proceedings of the 34th AAAI Conference on Artificial Intelligence (AAAI'20), 2020.[pdf] - Multi-Label Crowdsourcing Learning with Incomplete Annotations.
Shao-Yuan Li and Yuan Jiang.
In: Proceedings of the 15th Pacific Rim International Conference on Artificial Intelligence(PRICAI'18), 2018.
(Best Paper Award)[pdf] [code] - Obtaining high-quality label by distinguishing between easy and hard items in
crowdsourcing.
Wei Wang, Xiang-Yu Guo, Shao-Yuan Li, Yuan Jiang and Zhi-Hua Zhou.
In: Proceedings of the 26th International Joint Conference on Artificial Intelligence(IJCAI'17), 2017.[pdf]
- BayDNN: Friend
recommendation with Bayesian personalized ranking deep neural network.
Daizong Ding, Mi Zhang, Shao-Yuan Li, Jie Tang, Xiaotie Chen, and Zhi-Hua Zhou.
In: Proceedings of the 26th ACM International Conference on Information and Knowledge Management(CIKM'17), 2017. [pdf] - Partial View Clustering.
Shao-Yuan Li and Yuan Jiang and Zhi-Hua Zhou.
In: Proceedings of the 28th AAAI Conference on Artificial Intelligence(AAAI'14), 2014.[pdf] [code]
- Multi-Label Active Learning from Crowds.
Shao-Yuan Li , Yuan Jiang and Zhi-Hua Zhou
In: arXiv preprint arXiv:1508.00722, 2015.[pdf]
Honors
- 2023年AI华人女性青年学者
- 2023年第十八届“挑战杯”专项赛全国特等奖
- CVPR2023持续学习竞赛第四名
- IJCAI-ECAI 2022第一届噪声标记学习挖掘挑战赛两个任务亚军季军
- 2021年工信部海洋目标智能感知国际挑战赛三等奖
- Grand Prize Winner of PAKDD 2012 Data Mining Competition Open Category, 2012
- SME Segment Winner of PAKDD 2012 Data Mining Competition Open Category, 2012
- Scholarship for Outstanding Ph.D. Students Plan A, 2016
- PRICAI 2018 Best Pper Award, 2018
Professional Service
- Program Committee: ICML, NIPS, AAAI, IJCAI,KDD etc.
- Journal Reviwer: TPAMI, TKDE, TKDD, TNNLS etc.
Teaching
- The C Programming Language (for international undergraduate students, in English), Fall, 2019
- Academic English (for undergraduate students), Fall, 2019,2020,2021
- Pattern Recognition (for undergraduate students), Fall, 2020, 2021