Gengyu Lyu
School of Computer Sicence and Engineering, Beijing Jiaotong UniversityEmail: 18112030@bjtu.edu.cn; lyugengyu@gmail.com
Google Scholar Profile: scholar.google.com/citations?user=wZYLfyIAAAAJ&hl=zh-CN
RESEARCH INTEREST
Machine Learning and Data Mining, including Multi-Label Learning, Partial Label Learning, etc.
PUBLICATION
G. Lyu, S. Feng, T. Wang, C. Lang, Y. Li. GM-PLL: Graph Matching based Partial Label Learning. IEEE Transactions on Knowledge and Data Engineering. 2021
G. Lyu, S. Feng, Y. Li. Partial Multi-Label Learning via Probabilistic Graph Matching Mechanism. ACM SIGKDD Conference on Knowledge Discovery and Data Mining. 2020: 105-113
G. Lyu, X. Deng, Y. Wu, S. Feng. Beyond Shared Subspace: A View-Specific Fusion for Multi-View Multi-Label Learning. AAAI Conference on Artificial Intelligence. 2022
G. Lyu, S. Feng, Y. Jin, T. Wang, C. Lang, Y. Li. Prior Knowledge Regularized Self-Representation Model for Partial Multi-Label Learning. IEEE Transactions on Cybernetics. 2021
G. Lyu, S. Feng, T. Wang, C. Lang. A self-paced Regularization Framework for Partial Label Learning. IEEE Transactions on Cybernetics. 2020
G. Lyu, S. Feng, Y. Li. Partial Label Learning via Self-Paced Curriculum Strategy. The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. 2020
G. Lyu, S. Feng, Y. Li, Y. Jin, G. Dai, C. Lang. HERA: Partial Label Learning by Combining Heterogeneous Loss with Sparse and Low-Rank Regularization. ACM Transactions on Intelligent Systems and Technology. 11(3):1-34, 2020
G. Lyu, S. Feng, Y. Li, H. Liu, T. Wang. Noisy Label Tolerance: A new perspective of Partial Multi-Label Learning. Information Sciences. 2020
Z. Li*, G. Lyu*(equal contribution), S. Feng. Partial Multi-Label Learning via Multi-Subspace Representation. International Joint Conference on Artificial Intelligence. 2020: 2612-2618
Y. Sun*, G. Lyu* (equal contribution), S. Feng. Partial Label Learning via Subspace Representation and Global Disambiguation. The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases. 2020
Y. Wu, H. Liu, S. Feng, Y. Jin, G. Lyu, Z. Wu. GM-MLIC: Graph Matching based Multi-Label Image Classification. International Joint Conference on Artificial Intelligence. 2021
L. Sun, S. Feng, J. Liu, G. Lyu, C. Lang. Global-Local Label Correlation for Partial Multi-Label Learning. IEEE Transactions on Multimedia. 2020
RESEARCH PROJECTS
“Research on Partial Label Learning Algorithm”, Fundamental Research Funds for the Central Universities, 2018-2020, PI
“Research on Weakly Supervised Multi-Label Learning Algorithm”, Fundamental Research Funds for the Central Universities, 2020-2022, PI
“Research on Key Technologies of Large-Scale Image Semantic Understanding Under Weak Supervised Learning Framework”, National Natural Science Foundation of China, 2019-2022
“Research on Weakly Supervised Multi-Label Learning Algorithm and its Application in Image Semantic Understanding”, Beijing Natural Science Foundation , 2020-2022
“Research on Complex Scene based Unsupervised Transfer Learning Person Re-Identification Method”, National Natural Science Foundation of China, 2020-2023
“Research on Key Technologies of Image Saliency Detection and Segmentation Under Weak Supervised Learning Framework”, Beijing Natural Science Foundation , 2020-2022
PATENT
Noisy Label Tolerance based Partial Multi-Label Learning, 202010412161.7
PROFESSIONAL SERVICES
Conference PC Member (Reviewer): ICLR 2022; ICML 2021, 2022; NeurIPS 2021; CVPR 2021, 2022; ICCV 2021; AAAI 2021, 2022; IJCAI 2022; ECML-PKDD 2020;
Journal Reviewer: TPAMI, TNNLS, TMM;
AWARDS AND HONORS
Zhixing Scholarship (The highest honor of PhD graduates in BJTU) 2021
Baogang Scholarship 2021
National Scholarship 2014,2020
Huawei Scholarship 2021
Zhijin Scholarship 2020
First Prized Scholarship 2013, 2015, 2017, 2019
Outstanding Graduates in Beijing 2016
“Triple-A” Students in Beijing 2015