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)
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Authors
- 1. Yuhao Deng (Beijing Institute of Technology)
- 2. Chengliang Chai (Beijing Institute of Technology)
- 3. Kaisen Jin (Beijing Institute of Technology)
- 4. Linan Zheng (University of Arizona)
- 5. Lei Cao (Massachusetts Institute of Technology; University of Arizona)
- 6. Ye Yuan (Beijing Institute of Technology)
- 7. Guoren Wang (Beijing Institute of Technology)
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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Showing 6 of 6 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 18 | How Good Are Query Optimizers, Really? | 2016 | VLDB | 0.00059284255 |
| 582 | ActiveClean: Interactive Data Cleaning For Statistical Modeling | 2016 | VLDB | 0.00016148948 |
| 2,147 | Nearest Neighbor Classifiers over Incomplete Information: From Certain Answers to Certain Predictions | 2021 | VLDB | 9.0831495e-05 |
| 3,886 | GoodCore: Data-effective and Data-efficient Machine Learning through Coreset Selection over Incomplete Data | 2023 | SIGMOD | 7.0460597e-05 |
| 7,112 | Coresets over Multiple Tables for Feature-rich and Data-efficient Machine Learning | 2023 | VLDB | 5.6990782e-05 |
| 11,211 | MisDetect: Iterative Mislabel Detection using Early Loss | 2024 | VLDB | 5.093636e-05 |
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