% Key papers for Optimal stochastic bandit algorithms (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{neurips2017_minimal_56475,
  title = {{Minimal Exploration in Structured Stochastic Bandits}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/8966},
}

@inproceedings{aaai2016_algorithms_105040,
  title = {{Algorithms for Differentially Private Multi-Armed Bandits}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2016},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/10212},
}

@inproceedings{neurips2016_combinatorial_55628,
  title = {{Combinatorial Multi-Armed Bandit with General Reward Functions}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2016},
  url = {https://nips.cc/virtual/2016/poster/7046},
}

@inproceedings{neurips2016_on_55901,
  title = {{On Explore-Then-Commit strategies}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2016},
  url = {https://nips.cc/virtual/2016/poster/6978},
}

@inproceedings{aaai2018_efficient_103363,
  title = {{Efficient-UCBV: An Almost Optimal Algorithm Using Variance Estimates}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2018},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/12110},
}

@inproceedings{neurips2019_batched_57937,
  title = {{Batched Multi-armed Bandits Problem}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13215},
}

@inproceedings{neurips2019_linear_58550,
  title = {{Linear Stochastic Bandits Under Safety Constraints}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13965},
}

@inproceedings{neurips2016_multi_55880,
  title = {{Multi-armed Bandits: Competing with Optimal Sequences}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2016},
  url = {https://nips.cc/virtual/2016/poster/6990},
}

@inproceedings{neurips2017_improving_56377,
  title = {{Improving Regret Bounds for Combinatorial Semi-Bandits with Probabilistically Triggered Arms and Its Applications}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/8909},
}

@inproceedings{icml2016_anytime_35740,
  title = {{Anytime optimal algorithms in stochastic multi-armed bandits}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2016},
  url = {https://proceedings.mlr.press/v48/degenne16.html},
}

@inproceedings{aaai2021_regret_1247,
  title = {{Regret Bounds for Batched Bandits}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/07340-regret-bounds-for-batched-bandits/},
}

@inproceedings{icml2017_on_36316,
  title = {{On Kernelized Multi-armed Bandits}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2017},
  url = {https://icml.cc/virtual/2017/poster/779},
}

@inproceedings{aaai2017_achieving_104519,
  title = {{Achieving Privacy in the Adversarial Multi-Armed Bandit}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2017},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/10896},
}

@inproceedings{aaai2020_a_102314,
  title = {{A Near-Optimal Change-Detection Based Algorithm for Piecewise-Stationary Combinatorial Semi-Bandits}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2020},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/6176},
}

@inproceedings{neurips2018_almost_56859,
  title = {{Almost Optimal Algorithms for Linear Stochastic Bandits with Heavy-Tailed Payoffs}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11805},
}

@inproceedings{icml2019_optimal_37625,
  title = {{Optimal Algorithms for Lipschitz Bandits with Heavy-tailed Rewards}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/3798},
}

@inproceedings{neurips2017_position_56579,
  title = {{Position-based Multiple-play Bandit Problem with Unknown Position Bias}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/9276},
}

@inproceedings{neurips2019_phase_58799,
  title = {{Phase Transitions and Cyclic Phenomena in Bandits with Switching Constraints}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13835},
}

@inproceedings{neurips2022_on_66369,
  title = {{On Kernelized Multi-Armed Bandits with Constraints}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/53248},
}

@inproceedings{aaai2022_saving_2697,
  title = {{Saving Stochastic Bandits from Poisoning Attacks via Limited Data Verification}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2022},
  url = {https://aaai.org/papers/08054-saving-stochastic-bandits-from-poisoning-attacks-via-limited-data-verification/},
}

@inproceedings{aaai2024_multiobjective_6722,
  title = {{Multiobjective Lipschitz Bandits under Lexicographic Ordering}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29558},
}

@inproceedings{aaai2024_combinatorial_5428,
  title = {{Combinatorial Stochastic-Greedy Bandit}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29093},
}

@inproceedings{neurips2024_on_73093,
  title = {{On Weak Regret Analysis for Dueling Bandits}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94336},
}

@inproceedings{aaai2025_multiple_10074,
  title = {{Multiple Trade-offs: An Improved Approach for Lexicographic Linear Bandits}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/35491},
}

@inproceedings{iclr2024_combinatorial_34849,
  title = {{Combinatorial Bandits for Maximum Value Reward Function under Value-Index Feedback}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18225},
}

@inproceedings{aaai2025_batch_8231,
  title = {{Batch Ensemble for Variance Dependent Regret in Stochastic Bandits}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/33721},
}

@inproceedings{aaai2025_efficient_8907,
  title = {{Efficient Graph Bandit Learning with Side-Observations and Switching Constraints}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/33854},
}

@inproceedings{icml2025_fusing_48480,
  title = {{Fusing Reward and Dueling Feedback in Stochastic Bandits}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/44138},
}

@inproceedings{icml2026_improved_49764,
  title = {{Improved Algorithms for Nash Welfare in Linear Bandits}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=5WVIbxWqwA},
}

@inproceedings{icml2026_near_52612,
  title = {{Near-Optimal Regret for KL-Regularized Multi-Armed Bandits}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=XarOZG8Un0},
}

@inproceedings{neurips2024_on_70972,
  title = {{On the Minimax Regret for Contextual Linear Bandits and Multi-Armed Bandits with Expert Advice}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/96232},
}

@inproceedings{neurips2025_multimodal_75161,
  title = {{Multimodal Bandits: Regret Lower Bounds and Optimal Algorithms}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=4wnhbcppot},
}

@inproceedings{neurips2025_precise_75608,
  title = {{Precise Asymptotics and Refined Regret of Variance-Aware UCB}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=A0M3apV5zI},
}

@inproceedings{neurips2025_achieving_77400,
  title = {{Achieving \$tildemathcalO(1/N)\$ Optimality Gap in Restless Bandits through Gaussian Approximation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=TQNlIQIrcK},
}

@inproceedings{neurips2025_put_77905,
  title = {{Put CASH on Bandits: A Max K-Armed Problem for Automated Machine Learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=Yw9TdHy18N},
}

@inproceedings{neurips2025_does_78595,
  title = {{Does Stochastic Gradient really succeed for bandits?}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=gL4muAFwsh},
}

@inproceedings{neurips2025_a_79040,
  title = {{A Near-optimal, Scalable and Parallelizable Framework for Stochastic Bandits Robust to Adversarial Corruptions and Beyond}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=kzdLY8C8oa},
}

@inproceedings{neurips2025_pareto_79508,
  title = {{Pareto Optimal Risk-Agnostic Distributional Bandits with Heavy-Tail Rewards}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=q8oLLyA34Q},
}

@inproceedings{neurips2025_optimal_79677,
  title = {{Optimal Regret of Bandits under Differential Privacy}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=rmL109fdAJ},
}

@inproceedings{neurips2025_improved_79967,
  title = {{Improved Regret Bounds for Linear Bandits with Heavy-Tailed Rewards}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=uih8cWS3JF},
}