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

@inproceedings{icml2016_distributed_35800,
  title = {{Distributed Clustering of Linear Bandits in Peer to Peer Networks}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2016},
  url = {https://proceedings.mlr.press/v48/korda16.html},
}

@inproceedings{aaai2017_misspecified_103353,
  title = {{Misspecified Linear Bandits}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2017},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/11052},
}

@inproceedings{neurips2017_scalable_56650,
  title = {{Scalable Generalized Linear Bandits: Online Computation and Hashing}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/8808},
}

@inproceedings{icml2016_online_35935,
  title = {{Online Stochastic Linear Optimization under One-bit Feedback}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2016},
  url = {https://proceedings.mlr.press/v48/zhangb16.html},
}

@inproceedings{icml2020_meta_38450,
  title = {{Meta-learning with Stochastic Linear Bandits}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6532},
}

@inproceedings{icml2020_linear_38425,
  title = {{Linear bandits with Stochastic Delayed Feedback}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6130},
}

@inproceedings{icml2020_improved_38303,
  title = {{Improved Optimistic Algorithms for Logistic Bandits}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6154},
}

@inproceedings{neurips2021_an_63081,
  title = {{An Efficient Pessimistic-Optimistic Algorithm for Stochastic Linear Bandits with General Constraints}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/28796},
}

@inproceedings{aaai2016_linear_104982,
  title = {{Linear Submodular Bandits with a Knapsack Constraint}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2016},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/10154},
}

@inproceedings{neurips2020_high_60009,
  title = {{High-Dimensional Sparse Linear Bandits}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/17283},
}

@inproceedings{icml2019_bilinear_37193,
  title = {{Bilinear Bandits with Low-rank Structure}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/3780},
}

@inproceedings{aaai2020_safe_103329,
  title = {{Safe Linear Stochastic Bandits}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2020},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/6581},
}

@inproceedings{icml2016_no_35918,
  title = {{No-Regret Algorithms for Heavy-Tailed Linear Bandits}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2016},
  url = {https://proceedings.mlr.press/v48/medina16.html},
}

@inproceedings{neurips2020_stage_60863,
  title = {{Stage-wise Conservative Linear Bandits}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/18274},
}

@inproceedings{neurips2020_an_59366,
  title = {{An Asymptotically Optimal Primal-Dual Incremental Algorithm for Contextual Linear Bandits}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/19007},
}

@inproceedings{neurips2019_sequential_58978,
  title = {{Sequential Experimental Design for Transductive Linear Bandits}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/14072},
}

@inproceedings{icml2019_exploiting_37345,
  title = {{Exploiting structure of uncertainty for efficient matroid semi-bandits}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/3850},
}

@inproceedings{icml2021_adversarial_39031,
  title = {{Adversarial Combinatorial Bandits with General Non-linear Reward Functions}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2021},
  url = {https://icml.cc/virtual/2021/poster/8419},
}

@inproceedings{neurips2020_robust_60747,
  title = {{Robust and Heavy-Tailed Mean Estimation Made Simple, via Regret Minimization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/18094},
}

@inproceedings{neurips2022_batch_64034,
  title = {{Batch-Size Independent Regret Bounds for Combinatorial Semi-Bandits with Probabilistically Triggered Arms or Independent Arms}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/55015},
}

@inproceedings{aaai2024_hierarchize_6209,
  title = {{Hierarchize Pareto Dominance in Multi-Objective Stochastic Linear Bandits}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29030},
}

@inproceedings{aaai2024_new_6774,
  title = {{New Classes of the Greedy-Applicable Arm Feature Distributions in the Sparse Linear Bandit Problem}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29166},
}

@inproceedings{neurips2024_optimal_70314,
  title = {{Optimal Scalarizations for Sublinear Hypervolume Regret}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/96780},
}

@inproceedings{neurips2024_corruption_74456,
  title = {{Corruption-Robust Linear Bandits: Minimax Optimality and Gap-Dependent Misspecification}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93118},
}

@inproceedings{iclr2025_lasso_82904,
  title = {{Lasso Bandit with Compatibility Condition on Optimal Arm}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/28898},
}

@inproceedings{icml2024_stochastic_43359,
  title = {{Stochastic Bandits with ReLU Neural Networks}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/35093},
}

@inproceedings{icml2024_borda_43390,
  title = {{Borda Regret Minimization for Generalized Linear Dueling Bandits}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/35062},
}

@inproceedings{icml2024_high_43445,
  title = {{High-dimensional Linear Bandits with Knapsacks}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/35007},
}

@inproceedings{icml2024_optimal_43824,
  title = {{Optimal Batched Linear Bandits}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34628},
}

@inproceedings{icml2024_matroid_44234,
  title = {{Matroid Semi-Bandits in Sublinear Time}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34218},
}

@inproceedings{icml2024_efficient_44430,
  title = {{Efficient Low-Rank Matrix Estimation, Experimental Design, and Arm-Set-Dependent Low-Rank Bandits}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34022},
}

@inproceedings{icml2025_improved_46690,
  title = {{Improved Online Confidence Bounds for Multinomial Logistic Bandits}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/45882},
}

@inproceedings{icml2025_linear_47167,
  title = {{Linear Bandits with Partially Observable Features}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/45420},
}

@inproceedings{icml2025_contextual_49143,
  title = {{Contextual Linear Bandits with Delay as Payoff}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/43482},
}

@inproceedings{icml2026_stochastic_51293,
  title = {{Stochastic Linear Bandits with Parameter Noise}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=KfDXKFFzze},
}

@inproceedings{icml2026_robust_51973,
  title = {{Robust Linear Dueling Bandits with Post-serving Context under Unknown Delays and Adversarial Corruptions}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=RaJnDY8aAS},
}

@inproceedings{neurips2024_beyond_70294,
  title = {{Beyond task diversity: provable representation transfer for sequential multitask linear bandits}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/96798},
}

@inproceedings{neurips2024_generalized_71272,
  title = {{Generalized Linear Bandits with Limited Adaptivity}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95973},
}

@inproceedings{neurips2024_almost_71681,
  title = {{Almost Free: Self-concordance in Natural Exponential Families and an Application to Bandits}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95601},
}

@inproceedings{neurips2024_a_71749,
  title = {{A Unified Confidence Sequence for Generalized Linear Models, with Applications to Bandits}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95540},
}