About Me
Hi! I’m Shilong Bao(包世龙, E-mail: baoshilong@ucas.ac.cn). Now I am a Post-doc Fellow with the School of Computer Science and Technology, University of Chinese Academy of Sciences (UCAS). I got my Ph.D. degree in Institute of Information Engineering, Chinese Academy of Sciences (IIE, CAS), supervised by Prof. Qingming Huang (黄庆明) (IEEE Fellow). I am also lucky to have opportunities to collaborate with Qianqian Xu (许倩倩) (Professor at Institute of Computing Technology (ICT), CAS), Xiaochun Cao (操晓春) (Dean of School of Cyber Science and Technology, Sun Yat-sen University), Yuan He (何源) (Alibaba Group), Ke Ma (马坷) (Tenure-track Assistant Professor at UCAS), Zhiyong Yang (杨智勇) (Tenure-track Assistant Professor at UCAS).
My research interest includes machine learning and data mining. I have authored or co-authored several academic papers in top-tier international conferences and journals, including T-PAMI, ICML, NeurIPS, and ACM Multimedia.
🔥 News
- 2024.10.06: 🎉🎉 One papers have been accepted by NeurIPS 2024. Congrats to Boyu!
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2024.08.01: 🎉🎉 I am honored to be granted the Outstanding Doctoral Dissertation Award of Beijing Society of Image and Graphics (BSIG).
- 2024.06.08: 🎉🎉 One paper has been accepted by T-PAMI 2024. Congrats to all!
📝 Publications
The Minority Matters: A Diversity-Promoting Collaborative Metric Learning Algorithm.
Shilong Bao, Qianqian Xu, Zhiyong Yang , Yuan He, Xiaochun Cao, Qingming Huang. Advances in Neural Information Processing Systems (NeurIPS), 2451-2464, 2022. (Oral, 1.7%) | [Code]| [Video] | [Poster] | [Slides]
When All We Need is a Piece of the Pie: A Generic Framework for Optimizing Two-way Partial AUC.
Zhiyong Yang, Qianqian Xu, Shilong Bao, Yuan He, Xiaochun Cao and Qingming Huang. International Conference on Machine Learning (ICML), 11820–11829, 2021. (Long Talk, 3%) | [Code]| [Video] | [Poster] | [Slides]
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AUCSeg: AUC-oriented Pixel-level Long-tail Semantic Segmentation. Boyu Han, Qianqian Xu, Zhiyong Yang, Shilong Bao, Peisong Wen, Yangbangyan Jiang, Qingming Huang. Advances in Neural Information Processing Systems (NeurIPS), 2024. |[Code]|
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Improved Diversity-Promoting Collaborative Metric Learning for Recommendation. Shilong Bao, Qianqian Xu, Zhiyong Yang, Yuan He, Xiaochun Cao, and Qingming Huang. IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 2024. |[Code]|
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ReconBoost: Boosting Can Achieve Modality Reconcilement. Cong Hua, Qianqian Xu, Shilong Bao, Zhiyong Yang and Qingming Huang. International Conference on Machine Learning (ICML), 2024 | [Code] |
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Harnessing Hierarchical Label Distribution Variations in Test Agnostic Long-tail Recognition. Zhiyong Yang, Qianqian Xu, Zitai Wang, Sicong Li, Boyu Han, Shilong Bao, Xiaochun Cao and Qingming Huang. International Conference on Machine Learning (ICML), 2024 | [Code] |
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Revisiting AUC-oriented Adversarial Training with Loss-Agnostic Perturbations. Zhiyong Yang, Qianqian Xu, Wenzheng Hou, Shilong Bao, Yuan He, Xiaochun Cao and Qingming Huang. IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 2023. | [Code] |
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AUC-Oriented Domain Adaptation: From Theory to Algorithm. Zhiyong Yang, Qianqian Xu, Shilong Bao, Peisong Wen, Xiaochun Cao and Qingming Huang. IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 2023. | [Code] |
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Asymptotically Unbiased Instance-wise Regularized Partial AUC Optimization: Theory and Algorithm. Huiyang Shao, Qianqian Xu, Zhiyong Yang, Shilong Bao and Qingming Huang. Advances in Neural Information Processing Systems (NeurIPS), 38667–38679, 2022. | [Code] |
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Optimizing Two-way Partial AUC with an End-to-end Framework. Zhiyong Yang, Qianqian Xu, Shilong Bao, Yuan He, Xiaochun Cao and Qingming Huang. IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 10228-10246, 2022. | [Code] |
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AdAUC: End-to-end Adversarial AUC Optimization Against Long-tail Problems. Wenzheng Hou, Qianqian Xu, Zhiyong Yang, Shilong Bao, Yuan He and Qingming Huang. International Conference on Machine Learning (ICML), 8903–8925, 2022. | [Code] |
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Rethinking Collaborative Metric Learning: Toward an Efficient Alternative without Negative Sampling. Shilong Bao, Qianqian Xu, Zhiyong Yang, Xiaochun Cao and Qingming Huang. IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 1017–1035, 2022. |[Code]|
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Learning with Multiclass AUC: Theory and Algorithms. Zhiyong Yang, Qianqian Xu, Shilong Bao, Xiaochun Cao and Qingming Huang. IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI), 7747–7763, 2021. | [Code] |
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Collaborative Preference Embedding against Sparse Labels. Shilong Bao, Qianqian Xu, Ke Ma, Zhiyong Yang, Xiaochun Cao and Qingming Huang. ACM International Conference on Multimedia (ACM-MM), 2079–2087, 2019. | [Code]|
📖 Services
Conferences
- ICML: PC Member (2022, 2023, 2024)
- ICLR: PC Member (2024, 2025)
- AISTATS: PC Member (2025)
- NeurIPS: PC Member (2023, 2024)
- AAAI: PC Member (2023, 2024, 2025)
- CVPR: PC Member (2024)
Journals
- IEEE Transactions on Multimedia (T-MM): Reviewer
- IEEE Transactions on Circuits and Systems for Video Technology publication information (T-CSVT): Reviewer
- ACM Transactions on Multimedia Computing, Communications and Applications (TOMM): Reviewer
- Multimedia Systems: Reviewer
🎖 Honors and Awards
- 2024 Outstanding Doctoral Dissertation Award of Beijing Society of Image and Graphics (BSIG). (北京图象图形学学会优秀博士学位论文奖 (京津冀5篇))
- 2023 Zhuliyuehua Scholarship for Excellent Doctoral Student, CAS. (中国科学院朱李月华奖学金,中科院共300人)
- 2022 National Scholarship, Ministry of Education of the People’s Republic of China. (国家奖学金)
- 2021 Director Special Scholarship Award, IIE, CAS. (中科院信息工程研究所所长特别奖)
🎓 Educations
2019.09 - 2024.06, Ph.D. in Computer Applied Technology.
Institute of Information Engineering, Chinese Academy of Sciences (IIE, CAS).
University of Chinese Academy of Sciences, Beijing.
2015.09 - 2019.06, Undergraduate.
College of Computer Science and Technology.
Qingdao University (QDU), Qingdao.
💬 Invited Talks
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2023.02: AI TIME Youth PhD Talk of NeurIPS2022. [Video].
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2022.11: Oral presentation at NeurIPS conference [Video].
💻 Project
2020.02 - now: As a core member, I participated in the development of XCurve: Machine Learning with Decision-Invariant Metrics.
- Machine learning and deep learning technologies have recently been successfully employed in many complicated high-stake decision-making applications. The goal of Xcurve learning is to learn high-quality models that can adapt to different decision conditions, which provides a systematic solution to optimize the area under different kinds of performance curves. Welcome to try now and give us feedback!