Publications

2021-07-04 0 0 Comments Word Count: 877(words) Read Count: 4(minutes)

论文发表（Papers）

[12] Jun Yu, Yutong Dai, Xiaokang Liu, Jin Huang, Yishan Shen, Ke Zhang, Rong Zhou, Eashan Adhikarla, Wenxuan Ye, Yixin Liu, Zhaoming Kong, Kai Zhang, Yilong Yin, Vinod Namboodiri, Brian D. Davison, Jason H. Moore, and Yong Chen. "Unleashing the Power of Multi-Task Learning: A Comprehensive Survey Spanning Traditional, Deep, and Pretrained Foundation Model Eras" Submitted to Harvard Data Science Review (HDSR), 2024. [Paper] [Project]
[12] Jun Yu, Zhaoming Kong, Kun Chen, Xin Zhang, Yong Chen, and Lifang He. "A Multilinear Least-Squares Formulation for Sparse Tensor Canonical Correlation Analysis" In Transactions on Machine Learning Research (TMLR), 2024. [Paper] [Code]
[12] Eashan Adhikarla, Kai Zhang, Jun Yu, Lichao Sun, John Nicholson, Brian D. Davison. "Robust Computer Vision in an Ever-Changing World: A Survey of Techniques for Tackling Distribution Shifts" In arXiv, 2023. [Paper]
[13] Kai Zhang, Jun Yu, Eashan Adhikarla, Rong Zhou, Zhiling Yan, Yixin Liu, Zhengliang Liu, Lifang He, Brian Davison, Xiang Li, Hui Ren, Sunyang Fu, James Zou, Wei Liu, Jing Huang, Chen Chen, Yuyin Zhou, Tianming Liu, Xun Chen, Yong Chen, Quanzheng Li, Hongfang Liu, and Lichao Sun. "BiomedGPT: A Unified Biomedical Generative Pre-trained Transformer for Vision, Language, and Multimodal Tasks" In arXiv, 2023. [Paper] [Code]
[12] Zhaoming Kong, Fangxi Deng, Haomin Zhuang, Jun Yu, Lifang He, and Xiaowei Yang. "A Comparison of Image Denoising Methods" In arXiv, 2023. [Paper] [Code]
[11] Ce Zhou, Qian Li, Chen Li, Jun Yu, Yixin Liu, Guangjing Wang, Kai Zhang, Cheng Ji, Qiben Yan, Lifang He, Hao Peng, Jianxin Li, Jia Wu, Ziwei Liu, Pengtao Xie, Caiming Xiong, Jian Pei, Philip S. Yu, and Lichao Sun. (Equally Contributed). "A Comprehensive Survey on Pretrained Foundation Models: A History from BERT to ChatGPT" In arXiv, 2023. [Paper]
[10] Jun Yu, Benjamin Zalatan, Yong Chen, Li Shen, and Lifang He. "Tensor-Based Multi-Modal Multi-Target Regression for Alzheimer’s Disease Prediction" In 2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2022. 19.8% acceptance rate. [Paper] [Code] [Slides] [Video]
[9] 申朕, 崔超然, 董桂鑫, 余俊, 黄瑾, 尹义龙. 基于深度多任务学习的图像美感与情感联合预测研究. 软件学报，2022. Zhen Shen, Chaoran Cui, Guixin Dong, Jun Yu, Jin Huang, and Yilong Yin. Unified Image Aesthetic and Emotional Prediction Based on Deep Multi-task Learning. Ruan Jian Xue Bao/Journal of Software, 2022. DOI: 10.13328/j.cnki.jos.006487. [Paper]
[8] Jun Yu, Yong Chen, Li Shen, and Lifang He. "Tensor-Based Multi-Modality Multi-Target Regression for Alzheimer’s Disease Diagnosis." In 10th International Conference on Intelligent Biology and Medicine (ICIBM), 2022. Abstract Paper. [Paper] [Code] [Slides]
[7] Jun Yu. "Tensor Learning in Brain Network Analysis." Ph.D. student poster internal display. Computer Science & Engineering Department, Lehigh University. In Building C, May 9th, 2022. [Poster]	Nothing to show here. Please click on Poster.
[6] Jun Yu, Zhaoming Kong, Liang Zhan, Li Shen, and Lifang He. "Tensor-based Multi-Modality Feature Selection and Regression for Alzheimer’s Disease Diagnosis." In 8th International Conference on Bioinformatics & Biosciences (BIOS), 2022. [Paper] [Slides] [Code]
[5] Jun Yu, Zhaoming Kong, Aditya Kendre, Hao Peng, Carl Yang, Lichao Sun, Alex Leow, and Lifang He. "Structure-Preserving Graph Kernel for Brain Network Classification." In 19th IEEE International Symposium on Biomedical Imaging (ISBI), pp. 1-5. 2022. [Paper] [Poster] [Slides] [Video]
[4] 余俊. 基于深度多任务学习的图像美感和情感联合感知研究 [D]. 山东大学硕士毕业论文, 2020. Jun Yu. Research on Unified Aesthetics and Emotion Perception in Images Based on Deep Multi-Task Learning. Master Thesis. Shandong University, 2020. [Paper] [Code]
[3] Jin Huang, Chaoran Cui, Chunyun Zhang, Zhen Shen, Jun Yu, and Yilong Yin. "Learning Multi-Scale Attentive Features for Series Photo Selection." In 45th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 2742-2746. 2020. [Paper]
[2] Yuling Ma, Chaoran Cui, Jun Yu, Jie Guo, Gongping Yang, and Yilong Yin. "Multi-task MIML learning for pre-course student performance prediction." Frontiers of Computer Science 14, no. 5: 1-10. 2020. [Paper]
[1] Jun Yu, Chaoran Cui, LeiLei Geng, Yuling Ma, and Yilong Yin. "Towards Unified Aesthetics and Emotion Prediction in Images." In 26th IEEE International Conference on Image Processing (ICIP), pp. 2526-2530. 2019. [Paper] [Dataset] [Code]