% Key papers for Variance-reduced policy gradient (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{icml2017_stochastic_36415,
  title = {{Stochastic Variance Reduction Methods for Policy Evaluation}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2017},
  url = {https://icml.cc/virtual/2017/poster/648},
}

@inproceedings{iclr2020_reanalysis_29602,
  title = {{Reanalysis of Variance Reduced Temporal Difference Learning}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2020},
  url = {https://openreview.net/forum?id=S1ly10EKDS},
}

@inproceedings{icml2019_saga_37709,
  title = {{SAGA with Arbitrary Sampling}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/3969},
}

@inproceedings{icml2018_stochastic_37011,
  title = {{Stochastic Variance-Reduced Policy Gradient}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/2066},
}

@inproceedings{icml2020_momentum_38466,
  title = {{Momentum-Based Policy Gradient Methods}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6136},
}

@inproceedings{neurips2020_variance_61073,
  title = {{Variance-Reduced Off-Policy TDC Learning: Non-Asymptotic Convergence Analysis}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/18081},
}

@inproceedings{neurips2023_a_67337,
  title = {{A Smooth Binary Mechanism for Efficient Private Continual Observation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2023},
  url = {https://nips.cc/virtual/2023/poster/72389},
}

@inproceedings{iclr2022_bregman_31414,
  title = {{Bregman Gradient Policy Optimization}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2022},
  url = {https://iclr.cc/virtual/2022/poster/6662},
}

@inproceedings{icml2022_page_40981,
  title = {{PAGE-PG: A Simple and Loopless Variance-Reduced Policy Gradient Method with Probabilistic Gradient Estimation}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2022},
  url = {https://icml.cc/virtual/2022/poster/17219},
}

@inproceedings{icml2023_stochastic_42435,
  title = {{Stochastic Gradient Descent under Markovian Sampling Schemes}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2023},
  url = {https://icml.cc/virtual/2023/poster/24864},
}

@inproceedings{icml2025_nearly_48805,
  title = {{Nearly Optimal Sample Complexity for Learning with Label Proportions}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/43817},
}

@inproceedings{neurips2025_learning_74950,
  title = {{Learning from A Single Markovian Trajectory: Optimality and Variance Reduction}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=2oRz0NNOQQ},
}

@inproceedings{icml2025_learning_46800,
  title = {{Learning Robust Neural Processes with Risk-Averse Stochastic Optimization}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/45775},
}

@inproceedings{icml2026_variance_49861,
  title = {{Variance-Reduced \$(varepsilon, delta)-\$Unlearning using Forget Set Gradients}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=6XIwgtbcTa},
}

@inproceedings{neurips2019_variance_59173,
  title = {{Variance Reduced Policy Evaluation with Smooth Function Approximation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13703},
}

@inproceedings{neurips2020_an_59373,
  title = {{An Improved Analysis of  (Variance-Reduced) Policy Gradient and Natural Policy Gradient Methods}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/17486},
}

@inproceedings{neurips2022_the_65225,
  title = {{The Role of Baselines in Policy Gradient Optimization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/52917},
}