Research map / Learning theory and algorithms / Clustering
Fairness-constrained clustering
Cluster data with demographic fairness constraints using spectral, deep or variational methods.
19 accepted papers at ICML, NeurIPS, ICLR, CVPR and AAAI (2018–2026) · an approach in Clustering, keyword cluster “correlation clustering · hierarchical · spectral clustering”
State History Tried Checklist Preprints Who Export
Where it stands
Not enough benchmark data Fewer than four papers report the same benchmark, so there is no record to follow.
7 papers in 2023–24 and 3 in 2025–26 (at ICML, NeurIPS, ICLR, CVPR and AAAI); its share of the topic shrank, from 5.0% to 1.5%.
How this is decided
A benchmark is tracked when at least four papers of this approach report their own method on the same dataset and metric in at least two different years. Its record is the best number reported up to 2024 compared with the best reported in 2025–26: still improving means at least 1% better, flat means at most 0.2% better with at least two papers from 2025–26 trying. Numbers on a different scale from the rest (a fraction among percentages) and far outliers are left out. Results come from different papers with different setups, so they are signals, not head-to-head comparisons. The share of papers is counted at ICML, NeurIPS, ICLR, CVPR and AAAI.
How it got here
Most cited paper of each year
- 2018 · Clustering Redemption–Beyond the Impossibility of Kleinberg’s Axioms (NeurIPS 2018)
- 2019 · Guarantees for Spectral Clustering with Fairness Constraints (ICML 2019 · 43 citations)
- 2020 · Deep Fair Clustering for Visual Learning (CVPR 2020 · 61 citations)
- 2021 · Variational Fair Clustering (AAAI 2021 · 28 citations)
- 2022 · Modification-Fair Cluster Editing (AAAI 2022 · 4 citations)
- 2023 · Deep Fair Clustering via Maximizing and Minimizing Mutual Information: Theory, Algorithm and Metric (CVPR 2023 · 12 citations)
- 2024 · Towards Fairer Centroids in K-means Clustering (AAAI 2024 · 2 citations)
- 2025 · Fair Clustering via Alignment (ICML 2025 · 0 citations)
- 2026 · Riemannian Optimization for Fair Spectral Clustering (ICML 2026)
Earliest papers here
- Clustering Redemption–Beyond the Impossibility of Kleinberg’s Axioms (NeurIPS 2018)
- Guarantees for Spectral Clustering with Fairness Constraints (ICML 2019 · 43 citations)
- Deep Fair Clustering for Visual Learning (CVPR 2020 · 61 citations)
What has been tried
15 papers here report 120 measured changes (a component added, removed or swapped, compared with a baseline): helped 62%, no clear effect 7%, hurt 28%, mixed 4%. Papers mostly publish changes that helped, so "helped" is over-represented.
Ablations in recent papers
| What was changed | Measured on | Result | Effect | Paper |
|---|---|---|---|---|
| Increase λ from 0 (Lloyd’s heuristic) to positive values | Adult/sex, Adult/race, and CreditCard/SEX; fixed k · average cluster disparity | Helped | Towards Fairer Centroids in K-means Clustering (AAAI 2024 · 2 citations) | |
| Use Adam instead of Lloyd's algorithm for optimizing cluster centers | Fair clustering; datasets not specified in provided results · Cost | No clear effect | Fair Clustering via Alignment (ICML 2025 · 0 citations) |
What reviewers will expect
Datasets and baselines named in the 5 papers of this approach from 2024–2026 that have a full-text summary. Leaving out the common ones is a frequent review question.
Datasets
- Adult · 3 of 5 papers
Baselines
- FCBC · 2 of 5 papers
Recent preprints
Loading recent arXiv preprints…
Who publishes on it
Institutions on the most papers of this approach since 2023 (of 10 papers; from OpenAlex and the papers' affiliations).
- University of Maryland, College Park · 2 papers
- Optimized Markets · 2 papers
Use it
Download BibTeX of 19 key papersOpen the topic in the interactive map
Get alerts. Describe your idea in scime atlas and save it (free scime account): you get a weekly email when new preprints land close to it.
Related approaches
Same keyword cluster
- Clustering approximation algorithms (150 papers)
- Correlation clustering (102 papers)
- Subspace clustering (102 papers)
- Incomplete multi-view clustering (125 papers)
- Spectral clustering algorithms (43 papers)
Elsewhere in the topic
- Coresets and dynamic clustering (77 papers)
- k-means++ seeding analysis (76 papers)
- Fair clustering approximation (31 papers)
Benchmark numbers, ablations and baseline numbers are extracted by AI from each paper's full text and can be wrong; the paper is the authority. Data: results index of 2026-11-02, citation counts from OpenAlex (2026-10-09).