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

@inproceedings{neurips2019_making_58569,
  title = {{Making AI Forget You: Data Deletion in Machine Learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/14514},
}

@inproceedings{icml2018_massively_36841,
  title = {{Massively Parallel Algorithms and Hardness for Single-Linkage Clustering under \$ell\_p\$ Distances}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/2366},
}

@inproceedings{aaai2017_pive_101278,
  title = {{PIVE: Per-Iteration Visualization Environment for Real-Time Interactions with Dimension Reduction and Clustering}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2017},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/10628},
}

@inproceedings{icml2017_clustering_36092,
  title = {{Clustering High Dimensional Dynamic Data Streams}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2017},
  url = {https://icml.cc/virtual/2017/poster/626},
}

@inproceedings{icml2017_consistent_36110,
  title = {{Consistent k-Clustering}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2017},
  url = {https://icml.cc/virtual/2017/poster/588},
}

@inproceedings{neurips2018_distributed_57056,
  title = {{Distributed \$k\$-Clustering for Data with Heavy Noise}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11752},
}

@inproceedings{aaai2023_clustering_3264,
  title = {{Clustering What Matters: Optimal Approximation for Clustering with Outliers}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2023},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/25818},
}

@inproceedings{neurips2019_fully_58301,
  title = {{Fully Dynamic Consistent Facility Location}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13505},
}

@inproceedings{neurips2016_improving_55786,
  title = {{Improving PAC Exploration Using the Median Of Means}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2016},
  url = {https://nips.cc/virtual/2016/poster/6929},
}

@inproceedings{neurips2019_k_59216,
  title = {{k-Means Clustering of Lines for Big Data}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/14230},
}

@inproceedings{aaai2024_parameterized_6924,
  title = {{Parameterized Approximation Algorithms for Sum of Radii Clustering and Variants}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/30053},
}

@inproceedings{aaai2021_extreme_578,
  title = {{Extreme k-Center Clustering}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/03941-extreme-k-center-clustering/},
}

@inproceedings{icml2020_coresets_38060,
  title = {{Coresets for Clustering in Graphs of Bounded Treewidth}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6114},
}

@inproceedings{neurips2022_improved_64615,
  title = {{Improved Coresets for Euclidean \$k\$-Means}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/53216},
}

@inproceedings{aaai2022_parameterized_2538,
  title = {{Parameterized Approximation Algorithms for K-center Clustering and Variants}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2022},
  url = {https://aaai.org/papers/03895-parameterized-approximation-algorithms-for-k-center-clustering-and-variants/},
}

@inproceedings{aaai2024_near_6752,
  title = {{Near-Optimal Resilient Aggregation Rules for Distributed Learning Using 1-Center and 1-Mean Clustering with Outliers}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29584},
}

@inproceedings{cvpr2022_a_18209,
  title = {{A Sampling-Based Approach for Efficient Clustering in Large Datasets}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2022},
}

@inproceedings{icml2019_coresets_37253,
  title = {{Coresets for Ordered Weighted Clustering}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/3750},
}

@inproceedings{cvpr2024_probabilistic_24517,
  title = {{Probabilistic Sampling of Balanced K-Means using Adiabatic Quantum Computing}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/29421},
}

@inproceedings{neurips2022_coresets_66215,
  title = {{Coresets for Relational Data and The Applications}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/53540},
}

@inproceedings{aaai2024_universal_7706,
  title = {{Universal Weak Coreset}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29174},
}

@inproceedings{icml2025_almost_47327,
  title = {{Almost Optimal Fully Dynamic \$k\$-Center Clustering with Recourse}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/45262},
}

@inproceedings{aaai2024_approximate_5199,
  title = {{Approximate Distance Oracle for Fault-Tolerant Geometric Spanners}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29987},
}

@inproceedings{aaai2024_efficient_5804,
  title = {{Efficient Constrained K-center Clustering with Background Knowledge}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/30058},
}

@inproceedings{aaai2025_fully_9255,
  title = {{Fully-Scalable Massively Parallel Algorithm for k-center with Outliers}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/35454},
}

@inproceedings{aaai2025_improved_9518,
  title = {{Improved Fixed-Parameter Bounds for Min-Sum-Radii and Diameters k-Clustering and Their Fair Variants}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/33699},
}

@inproceedings{icml2024_faster_43546,
  title = {{Faster Streaming and Scalable Algorithms for Finding Directed Dense Subgraphs in Large Graphs}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34906},
}

@inproceedings{icml2025_faster_47949,
  title = {{Faster Approximation Algorithms for k-Center via Data Reduction}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/44656},
}

@inproceedings{icml2026_approximation_50160,
  title = {{Approximation Preserving Coresets}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=9YcP7zeO8h},
}

@inproceedings{icml2026_active_53721,
  title = {{Active Learning with Low-Rank Structure for Data Selection}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=i2SGjD0kIj},
}

@inproceedings{icml2026_quantum_54937,
  title = {{Quantum Algorithms for Triangle Cut Sparsification}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=u4klflLAX3},
}

@inproceedings{neurips2024_improved_71968,
  title = {{Improved Guarantees for Fully Dynamic \$k\$-Center Clustering with Outliers in General Metric Spaces}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95343},
}

@inproceedings{neurips2024_clustering_73684,
  title = {{Clustering with Non-adaptive Subset Queries}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93808},
}

@inproceedings{neurips2025_fast_76353,
  title = {{Fast Local Search Algorithms for Clustering with Adaptive Sampling and Bandit Strategies}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=ILf0VJYQBD},
}

@inproceedings{neurips2025_dynamic_77363,
  title = {{Dynamic Algorithm for Explainable \$k\$-medians Clustering under \$ell\_p\$ Norm}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=T1GXVrXJR4},
}

@inproceedings{neurips2025_dynamic_78181,
  title = {{Dynamic Diameter in High-Dimensions against Adaptive Adversary and Beyond}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=btW3QTadkW},
}

@inproceedings{neurips2025_a_79388,
  title = {{A Single-Swap Local Search Algorithm for k-Means of Lines}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=oo9IrVWcFL},
}