Jianglin (Johnny) Lu   盧江林Google Scholar   LinkedIn   Github
SMILE Lab, |
Latent Graph Inference with Limited Supervision.
[PDF][Project Page][Code] Jianglin Lu, Yi Xu, Huan Wang, Yue Bai, Yun Fu. Neural Information Processing Systems (NeurIPS), 2023. | |
Asymmetric Transfer Hashing with Adaptive Bipartite Graph Learning.
[PDF]
[Code] Jianglin Lu, Jie Zhou, Yudong Chen, Witold Pedrycz, Kwok-Wai Hung. IEEE Transactions on Cybernetics (TCYB), 2023. | |
Generalized Embedding Regression: A Framework for Supervised Feature Extraction.
[PDF]
[Code] Jianglin Lu, Zhihui Lai, Hailing Wang, Yudong Chen, Jie Zhou, Linlin Shen. IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2022. | |
Low-Rank Adaptive Graph Embedding for Unsupervised Feature Extraction.
[PDF]
[Code] Jianglin Lu, Hailing Wang, Jie Zhou, Yudong Chen, Zhihui Lai, Qinghua Hu. Pattern Recognition (PR), 2021. | |
Uncertainty-Guided Pixel Contrastive Learning for Semi-Supervised Medical Image Segmentation.
[PDF][Code] Tao Wang, Jianglin Lu, Zhihui Lai, Heng Kong, Jiajun Wen. International Joint Conference on Artificial Intelligence (IJCAI), 2022. | |
Local Graph Convolutional Networks for Cross-Modal Hashing.
[PDF][Code ] Yudong Chen, Sen Wang, Jianglin Lu, Zhi Chen, Zheng Zhang, Zi Huang. ACM International Conference on Multimedia (ACM MM), 2021. | |
Northeastern University Research Assitant, 01.2023--Now Supervisor: Yun Raymond Fu | |
Adobe Research Research Intern, 09.2024--11.2024 Mentors: Simon Jenni, Kushal Kafle, Jing Shi, Handong Zhao | |
Tencent Music Entertainment Research Intern, 11.2020--04.2021 Mentors: Kwok-Wai Hung, Simon Lui | |
Latent Graph Inference from Shallow Methods to GNNs [Slides], invited by Prof. Sarah Ostadabbas @ ACLab, Feb. 2024 |
Awesome Papers in Machine Learning, Computer Vision, Pattern Recognition, and Data Mining
[Link] |
Introduction to Vision Language Models [Notes] |
Introduction to Domain Adaptation [Notes] |
Introduction to Graph Neural Networks [Notes] |