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Two Birds with One Stone: Efficient Deep Learning over Mislabeled Data through Subset Selection

Summary: Deem selects a subset under label uncertainty by using losses and gradients to approximate the full gradient on soft labels. Framed as submodular NP-hard subset selection with a scalable approximation, it yields up to 10× speedups with no accuracy loss. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
hb36b7c137a37150a
Venue
SIGMOD
Year
2025
Pagerank
5.3739121e-05
Overall Rank
8,096 | 45.74%
DOI
10.1145/3728289

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{deng_sigmod25,
        title = {{Two Birds with One Stone: Efficient Deep Learning over Mislabeled Data through Subset Selection}},
        author = {Deng, Yuhao and Chai, Chengliang and Jin, Kaisen and Zheng, Linan and Cao, Lei and Yuan, Ye and Wang, Guoren},
        series = {{SIGMOD} '25},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3728289},
        url = {https://dl.acm.org/doi/10.1145/3728289},
        year = {2025}
}

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