Mining the Minoria: Unknown, Under-represented, and Under-performing Minority Groups
Summary: Propose “minority mining”: detect unknown, under‑represented and under‑performing subgroups from attribute‑only data by mapping to a dual space and exploiting hyperplane‑arrangement geometry. Provide an efficient low‑dim algorithm, a search‑based high‑dim heuristic to beat the curse of dimensionality, with theoretical analysis and empirical validation. (summarized by gpt-5-mini on Feb 09 2026)
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Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,223 | On Fair Epsilon Net and Geometric Hitting Set | 2026 | VLDB | 4.1945683e-05 |
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Outgoing Citations (Sorted by Pagerank)
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 |
|---|---|---|---|---|
| 1,940 | SliceLine: Fast, Linear-Algebra-based Slice Finding for ML Model Debugging | 2021 | SIGMOD | 0.00010020173 |
| 2,478 | Computing k-Regret Minimizing Sets | 2014 | VLDB | 8.6927744e-05 |
| 3,162 | Looking for Trouble: Analyzing Classifier Behavior via Pattern Divergence | 2021 | SIGMOD | 7.4589576e-05 |
| 4,749 | Slice Tuner: A Selective Data Acquisition Framework for Accurate and Fair Machine Learning Models | 2021 | SIGMOD | 5.9503689e-05 |
| 5,555 | On Obtaining Stable Rankings | 2019 | VLDB | 5.4386174e-05 |
| 6,816 | RRR: Rank-Regret Representative | 2019 | SIGMOD | 4.9173197e-05 |
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