Fair Clustering Repository
A curated, continuously-updated index of algorithmic fairness in clustering — definitions, contributions, and open problems for the TCS & ML communities.
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Publications
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Venues
Composition by fairness notion
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Fairness notion
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ADMIN
Review new papers, curate duplicates, pick papers to update the survey, or remove papers.
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Suggest a fairness notion
A new fairness notion becomes a new tag in the taxonomy, so it needs maintainer review. Please first check it isn't one of the existing notions: Group fairness (balance), Individual fairness, Socially fair (min-max), Proportional / core.
Opens a pre-filled GitHub issue labelled notion-proposal. A maintainer reviews it and, if accepted, adds the new tag to the taxonomy.
Submit a publication
Opens a pre-filled GitHub issue. Every submission is manually reviewed and approved by a maintainer before it appears — nothing is added automatically.
Suggest an edit
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Your suggestion opens a pre-filled GitHub issue. It is manually reviewed and approved by a maintainer before any change is applied.
Definition
Contribution
Open problems — one per line
Fairness notion
Nature of work
Propose a new tag
Changes to existing tags above are applied on merge. A brand-new tag is held for verification before it's added to the taxonomy.
Other comments — optional
New papers awaiting review ({{ pendingCount }})
Scraped by the discovery bot or submitted by users. Accept publishes to the repository (and queues it for the survey update); Reject removes it and blacklists it from future automatic suggestions (a user can still submit it manually). Partial reviews are fine — apply the ones you've decided and the rest stay queued. Applying opens a pull request: merge to finalize; once merged, decided papers leave this queue and accepted ones appear as normal papers.
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⚠ previously rejected/removed (resubmitted manually by a user)
No papers awaiting review.
Update the survey ({{ surveyQLen }} new)
Papers accepted since the survey was last updated. Copy the prompt, paste it to Claude to integrate them into the survey, then clear the queue.
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open ↗
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Queue is empty — the survey is up to date with all accepted papers.
Potential duplicate pairs ({{ dupCount }})
Title-similar papers already in the database. Use "Select to remove" to drop a true duplicate. IDs shown for reference.
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No title-similar pairs found.