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Gengyu Lyu 吕庚育

I am currently an Associate Professor (and a Ph.D. Supervisor) in the Faculty of Information Technology, Beijing University of Technology (BJUT), China. Before joining BJUT, I received my Ph.D. degree in the School of Computer and Information Technology, Beijing Jiaotong University in 2022, where I was fortunate to be supervised by Prof. Songhe Feng.

Here is my 中文简历.

 

Research Interests

My main research interests include Machine Learning and Data Mining, especially in learning from weakly supervised multi-label data.

  lyugengyu AT gmail DOT com and Google Scholar Citations Page                            

News

  • 2022.07 I joined the DMS Lab in BJUT.
  • 2022.05 One paper had been accepted by ACM TKDD.
  • 2022.04 One paper had been accepted by TMM.

Selected Publications

2022

Beyond Shared Subspace: A View-Specific Fusion for Multi-View Multi-Label Learning
Gengyu Lyu*, Xiang Deng*(Equal Contributions), Yanan Wu, Songhe Feng
AAAI Conference on Artificial Intelligence (AAAI) [PDF] [Codes]

Deep Graph Matching for Partial Label Learning
Gengyu Lyu*, Yanan Wu*(Equal Contributions), Songhe Feng
International Joint Conference on Artificial Intelligence (IJCAI) [PDF] [Codes]

A Self-Paced Regularization Framework for Partial Label Learning
Gengyu Lyu, Songhe Feng, Tao Wang, Congyan Lang
IEEE Transactions on Cybernetics (TCYB) [PDF]

Beyond Word Embeddings: Heterogeneous Prior Knowledge Driven Multi-Label Image Classification
Xiang Deng, Songhe Feng, Gengyu Lyu, Hongzhe Liu, Yi Jin
IEEE Transactions on Multimedia (TMM) [PDF]

Distance-Preserving Embedding Adaptive Bipartite Graph Multi-View Learning with Application to Multi-Label Classification
Xun Lu, Songhe Feng, Gengyu Lyu, Yi Jin, Congyan Lang
ACM Transactions on Knowledge Discovery from Data (TKDD) [PDF]

2021

GM-PLL: Graph Matching based Partial Label Learning
Gengyu Lyu, Songhe Feng, Tao Wang, Congyan Lang, Yidong Li
IEEE Transactions on Knowledge and Data Engineering (TKDE) [PDF] [Codes]

Prior Knowledge Regularized Self-Representation Model for Partial Multi-Label Learning
Gengyu Lyu, Songhe Feng, Yi Jin, Tao Wang, Congyan Lang, Yidong Li
IEEE Transactions on Cybernetics (TCYB) [PDF]

Noisy Label Tolerance: A New Perspective of Partial Multi-Label Learning
Gengyu Lyu, Songhe Feng, Yidong Li
Information Sciences (INS) [PDF] [Codes]

GM-MLIC: Graph Matching based Multi-Label Image Classification
Yanan Wu, He Liu, Songhe Feng, Yi Jin, Gengyu Lyu, Zizhang Wu
International Joint Conference on Artificial Intelligence (IJCAI) [PDF]

2020

Partial Multi-Label Learning via Probabilistic Graph Matching Mechanism
Gengyu Lyu, Songhe Feng, Yidong Li
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (ACM SIGKDD) [PDF] [Codes]

HERA: Partial Label Learning by Combining Heterogeneous Loss with Sparse and Low-rank Regularization
Gengyu Lyu, Songhe Feng, Yidong Li, Yi Jin, Guojun Dai, Congyan Lang
ACM Transactions on Intelligent Systems and Technology (ACM TIST) [PDF]

Partial Label Learning via Self-Paced Curriculum Strategy
Gengyu Lyu, Songhe Feng, Yidong Li
The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD) [PDF]

Partial Multi-Label Learning via Multi-Subspace Representation
Ziwei Li*, Gengyu Lyu*(Equal Contributions), Songhe Feng
International Joint Conference on Artificial Intelligence (IJCAI) [PDF]

Partial Label Learning via Subspace Representation and Global Disambiguation
Yue Sun*, Gengyu Lyu*(Equal Contributions), Songhe Feng
The European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD) [PDF]

Global-Local Label Correlation for Partial Multi-Label Learning
Lijuan Sun, Songhe Feng, Jun Liu, Gengyu Lyu, Congyan Lang
IEEE Transactions on Multimedia (TMM) [PDF]


Patents

  • Noisy Label Tolerance based Partial Multi-Label Learning Algorithm (No. 202010412161.7)

Selected Projects

  • Research on Partial Label Learning Algorithm, Fundamental Research Funds for the Central Universities, PI, 2018-2020
  • Research on Weakly Supervised Multi-Label Learning Algorithm, Fundamental Research Funds for the Central Universities, PI, 2020-2022
  • 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 Complex Scene based Unsupervised Transfer Learning Person Re-Identification Method, National Natural Science Foundation of China, 2020-2023
  • Research on Weakly Supervised Multi-Label Learning Algorithm and its Application in Image Semantic Understanding, Beijing Natural Science Foundation, 2020-2022
  • Research on Key Technologies of Image Saliency Detection and Segmentation Under Weak Supervised Learning Framework, Ministry of Education - China Mobile, 2018-2020

Professional Activities

Reviewer for Journals

  • IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
  • IEEE Transactions on Neural Networks and Learning Systems (TNNLS)
  • IEEE Transactions on Multimedia (TMM)
  • IEEE Transactions on Industrial Informatics (TII)
  • Information Sciences (INS)
  • Neurocomputing

Reviewer for Conferences

  • International Conference on Learning Representations (ICLR 2022, 2023)
  • International Conference on Machine Learning (ICML 2021, 2022)
  • Conference on Neural Information Processing Systems (NeurIPS 2021, 2022)
  • IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2021, 2022)
  • International Conference on Computer Vision (ICCV 2021)
  • European Conference on Computer Vision (ECCV 2022)
  • AAAI Conference on Artificial Intelligence (AAAI 2021, 2022, 2023)
  • International Joint Conference on Artificial Intelligence (IJCAI 2022)

Talks

  • Partial Multi-Label Learning via Multi-Subspace Representation – 2021 IJCAI-SAIA Young Elite Symposium, 2021
  • Partial Multi-Label Learning via Probabilistic Graph Matching Mechanism – ACM SIGKDD, 2020
  • Partial Label Learning via Self-Paced Curriculum Strategy – ECML-PKDD, 2020

Teaching Assistant

  • C Language Programming, Beijing Jiaotong University, 2017, 2018, 2019
  • Foundations of Computer Vision, Beijing Jiaotong University, 2019

Selected Awards

  • Excellent Doctor Degree Dissertation of BJTU (Jun. 2022)
  • BAOSTEEL Excellent Student Award (Nov. 2021)
  • ZHIXING Scholarship of BJTU (Jun. 2021 the greatest honor for the graduate students at BJTU)
  • China National Scholarship (Oct. 2020)
  • HUAWEI Scholarship (Oct. 2021)
  • PhD Innovation Fund of BJTU (Dec. 2018, Dec. 2020)
  • Excellent Graduates in Beijing (Jun. 2016, Jun. 2022)