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

@inproceedings{aaai2017_factorization_104559,
  title = {{Factorization Bandits for Interactive Recommendation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2017},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/10936},
}

@inproceedings{aaai2020_diversified_102069,
  title = {{Diversified Interactive Recommendation with Implicit Feedback}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2020},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/5931},
}

@inproceedings{icml2016_dcm_35783,
  title = {{DCM Bandits: Learning to Rank with Multiple Clicks}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2016},
  url = {https://proceedings.mlr.press/v48/katariya16.html},
}

@inproceedings{icml2017_online_36324,
  title = {{Online Learning to Rank in Stochastic Click Models}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2017},
  url = {https://icml.cc/virtual/2017/poster/645},
}

@inproceedings{aaai2017_sequential_100978,
  title = {{Sequential Peer Prediction: Learning to Elicit Effort using Posted Prices}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2017},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/10619},
}

@inproceedings{neurips2018_toprank_57713,
  title = {{TopRank: A practical algorithm for online stochastic ranking}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11392},
}

@inproceedings{aaai2021_a_26,
  title = {{A Hybrid Bandit Framework for Diversified Recommendation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/04036-a-hybrid-bandit-framework-for-diversified-recommendation/},
}

@inproceedings{aaai2022_achieving_1696,
  title = {{Achieving Counterfactual Fairness for Causal Bandit}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2022},
  url = {https://aaai.org/papers/06952-achieving-counterfactual-fairness-for-causal-bandit/},
}

@inproceedings{icml2016_bounded_35761,
  title = {{Bounded Off-Policy Evaluation with Missing Data for Course Recommendation and Curriculum Design}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2016},
  url = {https://proceedings.mlr.press/v48/hoiles16.html},
}

@inproceedings{icml2019_online_37618,
  title = {{Online Learning to Rank with Features}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/3782},
}

@inproceedings{neurips2017_real_56611,
  title = {{Real-Time Bidding with Side Information}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/9292},
}

@inproceedings{neurips2019_semi_58973,
  title = {{Semi-Parametric Dynamic Contextual Pricing}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13431},
}

@inproceedings{aaai2018_learning_102472,
  title = {{Learning to Interact With Learning Agents}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2018},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/11739},
}

@inproceedings{aaai2020_fatigue_101875,
  title = {{Fatigue-Aware Bandits for Dependent Click Models}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2020},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/5735},
}

@inproceedings{icml2016_barron_35751,
  title = {{Barron and Cover’s Theory in Supervised Learning and its Application to Lasso}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2016},
  url = {https://proceedings.mlr.press/v48/kawakita16.html},
}

@inproceedings{neurips2016_contextual_55645,
  title = {{Contextual semibandits via supervised learning oracles}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2016},
  url = {https://nips.cc/virtual/2016/poster/7069},
}

@inproceedings{iclr2023_online_32011,
  title = {{Online Low Rank Matrix Completion}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2023},
  url = {https://iclr.cc/virtual/2023/poster/11229},
}

@inproceedings{neurips2016_regret_55957,
  title = {{Regret Bounds for Non-decomposable Metrics with Missing Labels}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2016},
  url = {https://nips.cc/virtual/2016/poster/7338},
}

@inproceedings{icml2021_confidence_39158,
  title = {{Confidence-Budget Matching for Sequential Budgeted Learning}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2021},
  url = {https://icml.cc/virtual/2021/poster/9103},
}

@inproceedings{icml2021_context_39168,
  title = {{Context-Aware Online Collective Inference for Templated Graphical Models}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2021},
  url = {https://icml.cc/virtual/2021/poster/9525},
}

@inproceedings{icml2024_online_43572,
  title = {{Online Matrix Completion: A Collaborative Approach with Hott Items}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34880},
}

@inproceedings{icml2024_adaptively_44935,
  title = {{Adaptively Learning to Select-Rank in Online Platforms}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33517},
}

@inproceedings{icml2025_a_46722,
  title = {{A Parametric Contextual Online Learning Theory of Brokerage}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/45850},
}

@inproceedings{icml2026_keep_49441,
  title = {{Keep Everyone Happy: Online Fair Division of Numerous Items with Few Copies}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=2XMLJj67yY},
}

@inproceedings{neurips2025_contextual_78865,
  title = {{Contextual Online Pricing with (Biased) Offline Data}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=j9kTHUzEDX},
}

@inproceedings{neurips2025_statistical_79772,
  title = {{Statistical Parity with Exponential Weights}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=snWG3KVTQJ},
}

@inproceedings{iclr2025_dynamic_81309,
  title = {{Dynamic Assortment Selection and Pricing with Censored Preference Feedback}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/30462},
}

@inproceedings{iclr2025_finally_83259,
  title = {{Finally Rank-Breaking Conquers MNL Bandits: Optimal and Efficient Algorithms for MNL Assortment}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/28552},
}

@inproceedings{iclr2026_online_88538,
  title = {{Online Minimization of Polarization and Disagreement via Low-Rank Matrix Bandits}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=nwkiK8vNd1},
}

@inproceedings{neurips2026_learning_91065,
  title = {{Learning with Multiple Correct Answers - Regret Bounds under Different Feedback Models}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/153993},
}

@inproceedings{icml2025_online_47523,
  title = {{Online Linear Classification with Massart Noise}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/45073},
}

@inproceedings{iclr2025_efficient_83291,
  title = {{Efficient Top-m Data Values Identification for Data Selection}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/28522},
}

@inproceedings{neurips2026_dialbandit_91680,
  title = {{DialBandit: Adaptive Sequential Search with Tunable Evaluation Fidelity}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/149867},
}

@inproceedings{neurips2026_learning_94637,
  title = {{Learning from Ranking Feedback: Improved Regret Bounds via Independence Preserving Rank Breaking}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/153500},
}