Selected Publications

Yejia Liu, Jianyi Yang, Pengfei Li, Tongxin Li, Shaolei Ren (2024). Building Socially-Equitable Public Models. In ICML 2024.

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Yejia Liu, Pengfei Li, Daniel Wong, Shaolei Ren (2024). Geographical Server Relocation: Opportunities and Challenges. In HotCarbon 2024 (co-located with OSDI).

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Pengfei Li, Yejia Liu, Jianyi Yang, Shaolei Ren (2024). Towards Socially and Environmentally Responsible AI. In HotEthics 2024 (co-located with ASPLOS).

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Yejia Liu, Vidit Jain, Pengfei Li, Yinglun Zhu, Shaolei Ren (2024). LLM-Assisted Charging Scheduling for Decarbonizing Electrical Vehicle. In Submission.

Yejia Liu, Shijin Duan, Xiaolin Xu, Shaolei Ren (2024). Scheduled Knowledge Acquisition on Lightweight Vector Symbolic Architectures for Brain-Computer Interfaces. In TinyML 2024.

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Yejia Liu, Wang Zhu, Shaolei Ren (2022). Navigating Memory Construction by Global Pseudo-Task Simulation for Continual Learning. In NeurIPS 2022.

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Yejia Liu, Shijin Duan, Xiaolin Xu, Shaolei Ren (2022). MetaLDC: Meta Learning of Low-Dimensional Computing Classifiers for Fast On-Device Adaption. In TinyML 2023.

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Yejia Liu, Weiyuan Wu, Lampros Flokas, Jiannan Wang, Eugene Wu (2022). Enabling SQL-based Training Data Debugging for Federated Learning. In VLDB 2022.

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Shijin Duan, Yejia Liu, Shaolei Ren, Xiaolin Xu (2022). LeHDC: Learning-Based Hyperdimensional Computing Classifier. In DAC 2022.

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Lampros Flokas, Weiyuan Wu, Yejia Liu, Jiannan Wang, Eugene Wu (2022). Complaint-Driven Training Data Debugging at Interactive Speeds. In SIGMOD 2022.

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Yejia Liu, Oliver Schulte, Chao Li (2018). Model trees for identifying exceptional players in the NHL and NBA drafts. In MLSA@ECML-PKDD 2018.

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