% Key papers for Fair clustering approximation (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{icml2019_fair_37351,
  title = {{Fair k-Center Clustering for Data Summarization}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/4242},
}

@inproceedings{neurips2019_fair_58254,
  title = {{Fair Algorithms for Clustering}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13640},
}

@inproceedings{neurips2019_coresets_58055,
  title = {{Coresets for Clustering with Fairness Constraints}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13840},
}

@inproceedings{icml2019_scalable_37720,
  title = {{Scalable Fair Clustering}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/3962},
}

@inproceedings{icml2019_proportionally_37669,
  title = {{Proportionally Fair Clustering}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/4228},
}

@inproceedings{icml2020_individual_38316,
  title = {{Individual Fairness for k-Clustering}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6504},
}

@inproceedings{aaai2020_making_101923,
  title = {{Making Existing Clusterings Fairer: Algorithms, Complexity Results and Insights}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2020},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/5783},
}

@inproceedings{neurips2021_better_61809,
  title = {{Better Algorithms for Individually Fair \$k\$-Clustering}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/26620},
}

@inproceedings{icml2021_approximate_39055,
  title = {{Approximate Group Fairness for Clustering}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2021},
  url = {https://icml.cc/virtual/2021/poster/10725},
}

@inproceedings{icml2023_approximation_42698,
  title = {{Approximation Algorithms for Fair Range Clustering}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2023},
  url = {https://icml.cc/virtual/2023/poster/24457},
}

@inproceedings{aaai2024_towards_7628,
  title = {{Towards a Theoretical Understanding of Why Local Search Works for Clustering with Fair-Center Representation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29638},
}

@inproceedings{neurips2020_kfc_60122,
  title = {{KFC: A Scalable Approximation Algorithm for \$k\$−center Fair Clustering}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/17204},
}

@inproceedings{neurips2024_proportional_71638,
  title = {{Proportional Fairness in Clustering: A Social Choice Perspective}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95639},
}

@inproceedings{neurips2017_fair_56309,
  title = {{Fair Clustering Through Fairlets}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/9279},
}

@inproceedings{neurips2021_fair_62556,
  title = {{Fair Clustering Under a Bounded Cost}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/26483},
}

@inproceedings{icml2025_relative_46212,
  title = {{Relative Error Fair Clustering in the Weak-Strong Oracle Model}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/46348},
}

@inproceedings{icml2026_capacitated_50097,
  title = {{Capacitated Fair-Range Clustering: Hardness and Approximation Algorithms}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=91KRLNX4il},
}

@inproceedings{icml2026_fair_52056,
  title = {{Fair Transit Stop Placement: A Clustering Perspective and Beyond}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=SKH7vcWZSv},
}

@inproceedings{neurips2024_parameterized_72799,
  title = {{Parameterized Approximation Schemes for Fair-Range Clustering}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94597},
}

@inproceedings{neurips2025_unifying_79311,
  title = {{Unifying Proportional Fairness in Centroid and Non-Centroid Clustering}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=o7Z8TClGjp},
}

@inproceedings{iclr2025_relax_83392,
  title = {{Relax and Merge: A Simple Yet Effective Framework for Solving Fair \$k\$-Means and \$k\$-sparse Wasserstein Barycenter Problems}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/28424},
}

@inproceedings{aaai2026_matrix_106677,
  title = {{Matrix Editing Meets Fair Clustering: Parameterized Algorithms and Complexity}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/38984},
}

@inproceedings{aaai2026_generalizing_106770,
  title = {{Generalizing Fair Clustering to Multiple Groups: Algorithms and Applications}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/39077},
}

@inproceedings{aaai2026_linear_106850,
  title = {{Linear Time Algorithms for Individually Fair k-means via Multi-Swap Local Search}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/39202},
}

@inproceedings{aaai2026_fair_107311,
  title = {{Fair Model-based Clustering}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/39663},
}

@inproceedings{aaai2026_a_107542,
  title = {{A General Anchor-Based Framework for Scalable Fair Clustering}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/39894},
}

@inproceedings{aaai2026_improved_108670,
  title = {{Improved Streaming Algorithm for Fair k-Center Clustering}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/41022},
}

@inproceedings{iclr2025_fair_82368,
  title = {{Fair Clustering in the Sliding Window Model}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/29424},
}

@inproceedings{neurips2026_new_93472,
  title = {{New Coresets for Fair Clustering}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/152649},
}

@inproceedings{neurips2026_fair_93991,
  title = {{Fair Range k-Supplier Clustering in Offline and Streaming Models}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/153829},
}