% Key papers for Fixed-confidence versus fixed-budget identification (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{neurips2020_an_59375,
  title = {{An Optimal Elimination Algorithm for Learning a Best Arm}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/18817},
}

@inproceedings{icml2022_on_40936,
  title = {{On the Finite-Time Performance of the Knowledge Gradient Algorithm}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2022},
  url = {https://icml.cc/virtual/2022/poster/16171},
}

@inproceedings{neurips2022_top_66407,
  title = {{Top Two Algorithms Revisited}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/54319},
}

@inproceedings{aaai2025_quantum_10419,
  title = {{Quantum Best Arm Identification with Quantum Oracles}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/35432},
}

@inproceedings{neurips2022_multi_64824,
  title = {{Multi-Fidelity Best-Arm Identification}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/54031},
}

@inproceedings{icml2020_from_38233,
  title = {{From PAC to Instance-Optimal Sample Complexity in the Plackett-Luce Model}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/5831},
}

@inproceedings{neurips2019_maxgap_58580,
  title = {{MaxGap Bandit: Adaptive Algorithms for Approximate Ranking}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/14101},
}

@inproceedings{neurips2021_dealing_61224,
  title = {{Dealing With Misspecification In Fixed-Confidence Linear Top-m Identification}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/28129},
}

@inproceedings{neurips2021_selective_62638,
  title = {{Selective Sampling for Online Best-arm Identification}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/26801},
}

@inproceedings{neurips2022_minimax_65013,
  title = {{Minimax Optimal Algorithms for Fixed-Budget Best Arm Identification}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/53799},
}

@inproceedings{neurips2023_improving_67260,
  title = {{Improving the Knowledge Gradient Algorithm}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2023},
  url = {https://nips.cc/virtual/2023/poster/72457},
}

@inproceedings{neurips2024_optimal_73291,
  title = {{Optimal Multi-Fidelity Best-Arm Identification}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94150},
}

@inproceedings{icml2020_robust_38712,
  title = {{Robust Outlier Arm Identification}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/5992},
}

@inproceedings{icml2025_fixing_46549,
  title = {{Fixing the Loose Brake: Exponential-Tailed Stopping Time in Best Arm Identification}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/46019},
}

@inproceedings{icml2026_fixed_50546,
  title = {{Fixed Budget is No Harder Than Fixed Confidence in Best-Arm Identification up to Logarithmic Factors}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=DUmWdZetqZ},
}

@inproceedings{icml2026_box_52646,
  title = {{Box Thirding: Anytime Best Arm Identification under Insufficient Sampling}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=XoONWh8fbL},
}

@inproceedings{icml2026_cutting_55120,
  title = {{Cutting LLM Evaluation Costs with SySRs: A Bandit Algorithm That Provably Exploits Model Similarity}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=vkG1xVVKOH},
}

@inproceedings{icml2026_optimal_55327,
  title = {{Optimal Top-\$k\$ Identification from Pairwise Comparisons}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=xnrxwwAKz5},
}

@inproceedings{neurips2021_online_61358,
  title = {{Online Sign Identification: Minimization of the Number of Errors in Thresholding Bandits}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/27725},
}

@inproceedings{neurips2023_non_67321,
  title = {{Non-Asymptotic Analysis of a UCB-based Top Two Algorithm}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2023},
  url = {https://nips.cc/virtual/2023/poster/72404},
}

@inproceedings{neurips2024_fixed_73367,
  title = {{Fixed Confidence Best Arm Identification in the Bayesian Setting}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94082},
}

@inproceedings{iclr2026_best_87304,
  title = {{Best-of-Majority: Minimax-Optimal Strategy for Pass@k Inference Scaling}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=a6CVQpjbXq},
}

@inproceedings{neurips2026_does_91325,
  title = {{Does 1/2-Tsallis-INF Also Work Well for Best-Arm Identification?}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/150443},
}

@inproceedings{neurips2026_nearly_91562,
  title = {{Nearly Optimal Fixed-Confidence Best-Arm Identification with 1-Bit Feedback}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/155304},
}

@inproceedings{aaai2026_constrained_106756,
  title = {{Constrained Best Arm Identification with Tests for Feasibility}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/39063},
}

@inproceedings{aaai2026_best_106837,
  title = {{Best Arm Identification with Biased Contexts}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/39189},
}

@inproceedings{icml2026_learning_52780,
  title = {{Learning the Best Under Constraints: A Duality-Based Framework}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=Z15BvlGl1S},
}

@inproceedings{neurips2026_quantum_90021,
  title = {{Quantum Speedup of Multi-armed Bandits at Scale by Tackling Memory Decoherence}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/154155},
}

@inproceedings{neurips2026_quantum_91287,
  title = {{Quantum Best Arm Identification with Limited Round of Adaptivity: Lower Bounds and Algorithms}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/148383},
}

@inproceedings{neurips2026_marc_92288,
  title = {{marc.jourdan@epfl.ch}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/156663},
}

@inproceedings{neurips2026_target_92662,
  title = {{Target-Budget Best-Function Identification for Scaling-Law-Guided Model Selection}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/152616},
}

@inproceedings{neurips2026_sharp_94812,
  title = {{Sharp Non-Asymptotic Analysis of the Penalized Challenger in \$beta\$-EB-TCI for Bernoulli Bandits}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/150746},
}