3504 Wegmans Hall
University of Rochester
Rochester, NY 14627
jlin81 AT ur.rochester.edu
I am a second-year Ph.D. student at University of Rochester, advised by Prof. Jiebo Luo. Before that, I received the B.Eng. degree in software engineering and M.Sc. degree in computational mathematics all from the Sun Yat-sen University, supervised by Prof. Hongyang Chao. I also worked as a research intern at JD AI Research, co-advised by Dr. Yu Wang, Dr. Ting Yao, and Dr. Tao Mei.
My research focuses on machine learning and computer vision, especially in vision-and-language, video analysis, health care, self-supervised learning, and out-of-distribution analysis.
May. 2023 | One paper is accepted by ICDH 2023. |
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Sep. 2022 | One paper is accepted by NeurIPS 2022. |
Jun. 2022 | One paper is accepted by TPAMI. |
Sep. 2021 | One paper is accepted by NeurIPS 2021. |
* indicates equal contribution
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VideoXum: Cross-modal Visual and Textural Summarization of Videos
Preprint. [PDF] |
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Predicting Adverse Neonatal Outcomes for Preterm Neonates with Multi-Task Learning
IEEE International Conference on Digital Health. ICDH 2023. [PDF] |
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Out-of-Distribution Detection via Conditional Kernel Independence Model
Neural Information Processing Systems. NeurIPS 2022. [PDF] [Code] Spotlight Presentation |
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Out-of-Distribution Detection with Hilbert-Schmidt Independence Optimization
Preprint. [PDF] [Code] |
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A Low Rank Promoting Prior for Contrastive Learning
IEEE Transactions on Pattern Analysis and Machine Intelligence. TPAMI 2021. [PDF] [Code] |
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Improving Self-supervised Learning with Automated Unsupervised Outlier Arbitration
Neural Information Processing Systems. NeurIPS 2021. [PDF] [Code] |
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CORE-Text: Improving Scene Text Detection with Contrastive Relational Reasoning
IEEE International Conference on Multimedia and Expo. ICME 2021. [PDF] [Code] Oral Presentation |
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Improving Fast Segmentation With Teacher-student Learning
BMVC 2018.
[PDF] |
British Machine Vision Conference.
Last updated on Aug 2023.
Copyright © Jingyang Lin