I am fortunate to be advised by Prof. Xiang-Yang Li and Prof. Lan Zhang at USTC. My research interest is building resource-efficient networking systems for machine-learning model inference.
Selected Publications
Secure Transformer Inference
Mu Yuan, Lan Zhang, Xiang-Yang Li
preprint
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| Code
PacketGame: Multi-Stream Packet Gating for Concurrent Video Inference at Scale
Mu Yuan, Lan Zhang, Xuanke You, Xiang-Yang Li
ACM SIGCOMM 2023 (SIG Grant Award)
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| Code
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Mu Yuan, Lan Zhang, Xuanke You, and Xiang-Yang Li. 2023. PacketGame: Multi-Stream Packet Gating for Concurrent Video Inference at Scale. In Proceedings of the ACM SIGCOMM 2023 Conference (ACM SIGCOMM '23). Association for Computing Machinery, New York, NY, USA, 724–737. https://doi.org/10.1145/3603269.3604825
@inproceedings{yuan-packetgame,
author = {Yuan, Mu and Zhang, Lan and You, Xuanke and Li, Xiang-Yang},
title = {PacketGame: Multi-Stream Packet Gating for Concurrent Video Inference at Scale},
year = {2023},
isbn = {9798400702365},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3603269.3604825},
doi = {10.1145/3603269.3604825},
booktitle = {Proceedings of the ACM SIGCOMM 2023 Conference},
pages = {724–737},
numpages = {14},
location = {New York, NY, USA},
series = {ACM SIGCOMM '23}
}
MLink: Linking Black-Box Models from Multiple Domains for Collaborative Inference
Mu Yuan, Lan Zhang, Zimu Zheng, Yi-Nan Zhang, Xiang-Yang Li
IEEE TPAMI 2023
PDF
| Cite
M. Yuan, L. Zhang, Z. Zheng, Y. -N. Zhang and X. -Y. Li, "MLink: Linking Black-Box Models From Multiple Domains for Collaborative Inference," in IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 45, no. 10, pp. 12085-12097, Oct. 2023, doi: 10.1109/TPAMI.2023.3283780.
@ARTICLE{yuan-mlink-tpami,
author={Yuan, Mu and Zhang, Lan and Zheng, Zimu and Zhang, Yi-Nan and Li, Xiang-Yang},
journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
title={MLink: Linking Black-Box Models From Multiple Domains for Collaborative Inference},
year={2023},
volume={45},
number={10},
pages={12085-12097},
doi={10.1109/TPAMI.2023.3283780}}
InFi: End-to-End Learning to Filter Input for Resource-Efficiency in Mobile-Centric Inference
Mu Yuan, Lan Zhang, Fengxiang He, Xueting Tong, Miao-Hui Song, Zhengyuan Xu, Xiang-Yang Li
IEEE TMC 2023
PDF
CoTel: Ontology-Neural Co-Enhanced Text Labeling
Miao-Hui Song, Lan Zhang, Mu Yuan, Zichong Li, Qi Song, Yijun Liu, Guidong Zheng
ACM WWW 2023
Efficient Deep Ensemble Inference via Query Difficulty-dependent Task Scheduling
Zichong Li, Lan Zhang, Mu Yuan, Miao-Hui Song, Qi Song
IEEE ICDE 2023
MLink: Linking Black-box Models for Collaborative Multi-model Inference
Mu Yuan, Lan Zhang, Xiang-Yang Li
AAAI 2022 (Oral 4.5%)
PDF
| Slides (20min version)
| Slides (1min version)
| Code
| Bilibili
| Cite
Mu Yuan, Lan Zhang, and Xiang-Yang Li. 2022. “MLink: Linking Black-Box Models for Collaborative Multi-Model Inference”. Proceedings of the AAAI Conference on Artificial Intelligence 36 (9):9475-83. https://doi.org/10.1609/aaai.v36i9.21180.
@article{yuan-mlink,
title={MLink: Linking Black-Box Models for Collaborative Multi-Model Inference},
volume={36},
url={https://ojs.aaai.org/index.php/AAAI/article/view/21180},
DOI={10.1609/aaai.v36i9.21180},
number={9},
journal={Proceedings of the AAAI Conference on Artificial Intelligence},
author={Yuan, Mu and Zhang, Lan and Li, Xiang-Yang},
year={2022},
month={Jun.},
pages={9475-9483}
}
InFi: End-to-end Learnable Input Filter for Resource-efficient Mobile-centric Inference
Mu Yuan, Lan Zhang, Fengxiang He, Xueting Tong, Xiang-Yang Li
ACM MobiCom 2022
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| Code
| Bilibili
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Mu Yuan, Lan Zhang, Fengxiang He, Xueting Tong, and Xiang-Yang Li. 2022. InFi: end-to-end learnable input filter for resource-efficient mobile-centric inference. In Proceedings of the 28th Annual International Conference on Mobile Computing And Networking (MobiCom '22). Association for Computing Machinery, New York, NY, USA, 228–241. https://doi.org/10.1145/3495243.3517016.
@inproceedings{yuan-infi,
author = {Yuan, Mu and Zhang, Lan and He, Fengxiang and Tong, Xueting and Li, Xiang-Yang},
title = {InFi: End-to-End Learnable Input Filter for Resource-Efficient Mobile-Centric Inference},
year = {2022},
isbn = {9781450391818},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3495243.3517016},
doi = {10.1145/3495243.3517016},
booktitle = {Proceedings of the 28th Annual International Conference on Mobile Computing And Networking},
pages = {228–241},
numpages = {14},
location = {Sydney, NSW, Australia},
series = {MobiCom '22}
}
Adaptive Model Scheduling for Resource-efficient Data Labeling
Mu Yuan, Lan Zhang, Xiang-Yang Li, Lin-Zhuo Yang, Hui Xiong
ACM TKDD 2022
PDF
| Cite
Mu Yuan, Lan Zhang, Xiang-Yang Li, Lin-Zhuo Yang, and Hui Xiong. 2022. Adaptive Model Scheduling for Resource-efficient Data Labeling. ACM Trans. Knowl. Discov. Data 16, 4, Article 71 (August 2022), 22 pages. https://doi.org/10.1145/3494559.
@article{yuan-adms-tkdd,
author = {Yuan, Mu and Zhang, Lan and Li, Xiang-Yang and Yang, Lin-Zhuo and Xiong, Hui},
title = {Adaptive Model Scheduling for Resource-Efficient Data Labeling},
year = {2022},
issue_date = {August 2022},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
volume = {16},
number = {4},
issn = {1556-4681},
url = {https://doi.org/10.1145/3494559},
doi = {10.1145/3494559},
journal = {ACM Trans. Knowl. Discov. Data},
month = {jan},
articleno = {71},
numpages = {22},
keywords = {Model scheduling, reinforcement learning, data labeling}
}
High-quality Activity-Level Video Advertising
Mu Yuan, Lan Zhang, Zhengtao Wu, Daren Zheng
IEEE/ACM IWQoS 2020 (Video Presentation Award)
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| Bilibili
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Mu Yuan, Lan Zhang, Zhengtao Wu and Daren Zheng, "High-quality Activity-Level Video Advertising," 2020 IEEE/ACM 28th International Symposium on Quality of Service (IWQoS), Hang Zhou, China, 2020, pp. 1-10, doi: 10.1109/IWQoS49365.2020.9212956.
@INPROCEEDINGS{yuan-actva,
author={Yuan, Mu and Zhang, Lan and Wu, Zhengtao and Zheng, Daren},
booktitle={2020 IEEE/ACM 28th International Symposium on Quality of Service (IWQoS)},
title={High-quality Activity-Level Video Advertising},
year={2020},
pages={1-10},
doi={10.1109/IWQoS49365.2020.9212956}
}
Comprehensive and Efficient Data Labeling via Adaptive Model Scheduling
Mu Yuan, Lan Zhang, Xiang-Yang Li, Hui Xiong
IEEE ICDE 2020
PDF
| Official Video
| Bilibili
| Slides
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Mu Yuan, Lan Zhang, Xiang-Yang Li and Hui Xiong, "Comprehensive and Efficient Data Labeling via Adaptive Model Scheduling," 2020 IEEE 36th International Conference on Data Engineering (ICDE), Dallas, TX, USA, 2020, pp. 1858-1861, doi: 10.1109/ICDE48307.2020.00188.
@INPROCEEDINGS{yuan-adms-icde,
author={Yuan, Mu and Zhang, Lan and Li, Xiang-Yang and Xiong, Hui},
booktitle={2020 IEEE 36th International Conference on Data Engineering (ICDE)},
title={Comprehensive and Efficient Data Labeling via Adaptive Model Scheduling},
year={2020},
volume={},
number={},
pages={1858-1861},
doi={10.1109/ICDE48307.2020.00188}
}
Services
TPC of AAAI 2023/2024
Associate Editor of IEEE IoT Journal, Reviewer of ACM IMWUT 2022, Frontiers of Computer Science
Awards
2023 ByteDance Scholars Award (13 Nationwide) [Link]
2023 Baosteel Scholarship
2023/2022/2020 National Scholarship [Link]
2019 Outstanding Graduate Award [Link]
2018 Yuan-Qing Scholarship [Link]
2018 SenseTime Scholarship (22 Nationwide) [Link]
2018 Grand Price (1 out of 1530 teams) of the 4th National University Cloud Computing Contest [Link]
