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

@inproceedings{icml2018_sbeed_36968,
  title = {{SBEED: Convergent Reinforcement Learning with Nonlinear Function Approximation}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/2441},
}

@inproceedings{icml2019_sample_37719,
  title = {{Sample-Optimal Parametric Q-Learning Using Linearly Additive Features}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/3991},
}

@inproceedings{neurips2020_sample_60772,
  title = {{Sample Complexity of Asynchronous Q-Learning: Sharper Analysis and Variance Reduction}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/17971},
}

@inproceedings{icml2021_bilinear_39103,
  title = {{Bilinear Classes: A Structural Framework for Provable Generalization in RL}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2021},
  url = {https://icml.cc/virtual/2021/poster/9125},
}

@inproceedings{neurips2018_q_57539,
  title = {{Q-learning with Nearest Neighbors}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11316},
}

@inproceedings{neurips2020_sample_60774,
  title = {{Sample Efficient Reinforcement Learning via Low-Rank Matrix Estimation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/18391},
}

@inproceedings{neurips2020_planning_60586,
  title = {{Planning in Markov Decision Processes with Gap-Dependent Sample Complexity}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/18528},
}

@inproceedings{icml2021_tightening_40032,
  title = {{Tightening the Dependence on Horizon in the Sample Complexity of Q-Learning}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2021},
  url = {https://icml.cc/virtual/2021/poster/8929},
}

@inproceedings{neurips2020_agnostic_59355,
  title = {{Agnostic \$Q\$-learning with Function Approximation in Deterministic Systems: Near-Optimal Bounds on Approximation Error and Sample Complexity}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/17000},
}

@inproceedings{neurips2017_learning_56424,
  title = {{Learning Linear Dynamical Systems via Spectral Filtering}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/9438},
}

@inproceedings{aaai2023_global_3779,
  title = {{Global Convergence of Two-Timescale Actor-Critic for Solving Linear Quadratic Regulator}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2023},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/25865},
}

@inproceedings{neurips2021_finite_62798,
  title = {{Finite-Sample Analysis of Off-Policy TD-Learning via Generalized Bellman Operators}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/27957},
}

@inproceedings{neurips2022_on_64184,
  title = {{On the Sample Complexity of Stabilizing LTI Systems on a Single Trajectory}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/53816},
}

@inproceedings{neurips2022_near_65280,
  title = {{Near-Optimal Sample Complexity Bounds for Constrained MDPs}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/54030},
}

@inproceedings{iclr2021_efficient_30703,
  title = {{Efficient Empowerment Estimation for Unsupervised Stabilization}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2021},
  url = {https://iclr.cc/virtual/2021/poster/3285},
}

@inproceedings{iclr2022_per_30785,
  title = {{PER-ETD: A Polynomially Efficient Emphatic Temporal Difference Learning Method}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2022},
  url = {https://iclr.cc/virtual/2022/poster/6938},
}

@inproceedings{icml2021_task_40001,
  title = {{Task-Optimal Exploration in Linear Dynamical Systems}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2021},
  url = {https://icml.cc/virtual/2021/poster/8917},
}

@inproceedings{neurips2020_slip_60764,
  title = {{SLIP: Learning to predict in unknown dynamical systems with long-term memory}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/18349},
}

@inproceedings{neurips2023_sample_67444,
  title = {{Sample Complexity of Goal-Conditioned Hierarchical Reinforcement Learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2023},
  url = {https://nips.cc/virtual/2023/poster/72289},
}

@inproceedings{iclr2024_optimal_35051,
  title = {{Optimal Sample Complexity for Average Reward Markov Decision Processes}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18023},
}

@inproceedings{aaai2025_two_11120,
  title = {{Two-Timescale Critic-Actor for Average Reward MDPs with Function Approximation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/34182},
}

@inproceedings{icml2024_an_44919,
  title = {{An Improved Finite-time Analysis of Temporal Difference Learning with Deep Neural Networks}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33533},
}

@inproceedings{icml2024_closing_45495,
  title = {{Closing the Gap: Achieving Global Convergence (Last Iterate) of Actor-Critic under Markovian Sampling with Neural Network Parametrization}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/32956},
}

@inproceedings{icml2025_near_46508,
  title = {{Near-Optimal Sample Complexity for MDPs via Anchoring}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/46059},
}

@inproceedings{icml2026_the_54726,
  title = {{The Optimal Sample Complexity of Linear Contracts}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=ry5HitnXzc},
}

@inproceedings{neurips2024_randomized_72465,
  title = {{Randomized algorithms and PAC bounds for inverse reinforcement learning in continuous spaces}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94893},
}

@inproceedings{neurips2025_a_74945,
  title = {{A Finite Sample Analysis of Distributional TD Learning with Linear Function Approximation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=2lNCktd2c3},
}

@inproceedings{neurips2025_stabilizing_76589,
  title = {{Stabilizing LTI Systems under Partial Observability: Sample Complexity and Fundamental Limits}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=KwHsZJatB8},
}

@inproceedings{neurips2025_on_78691,
  title = {{On the Sample Complexity Bounds of Bilevel Reinforcement Learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=hNh3V1DXs5},
}

@inproceedings{neurips2025_reliably_78752,
  title = {{Reliably detecting model failures in deployment without labels}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=hwRVeHkLvO},
}

@inproceedings{iclr2026_dimension_89126,
  title = {{Dimension-Free Decision Calibration for Nonlinear Loss Functions}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=vAU1fo1zRV},
}

@inproceedings{icml2026_efficiently_49258,
  title = {{Efficiently Solving Discounted MDPs via Predictions with Unknown Prediction Errors}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=0nrxgFZEEq},
}