% Key papers for Proximal finite-sum methods (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{neurips2017_non_56516,
  title = {{Non-convex Finite-Sum Optimization Via SCSG Methods}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/9022},
}

@inproceedings{icml2016_variance_36025,
  title = {{Variance Reduction for Faster Non-Convex Optimization}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2016},
  url = {https://proceedings.mlr.press/v48/allen-zhua16.html},
}

@inproceedings{neurips2016_proximal_55948,
  title = {{Proximal Stochastic Methods for Nonsmooth Nonconvex Finite-Sum Optimization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2016},
  url = {https://nips.cc/virtual/2016/poster/6920},
}

@inproceedings{neurips2018_a_56809,
  title = {{A Simple Proximal Stochastic Gradient Method for Nonsmooth Nonconvex Optimization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11543},
}

@inproceedings{neurips2016_a_55545,
  title = {{A Simple Practical Accelerated Method for Finite Sums}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2016},
  url = {https://nips.cc/virtual/2016/poster/6921},
}

@inproceedings{icml2017_convergence_36114,
  title = {{Convergence Analysis of Proximal Gradient with Momentum for Nonconvex Optimization}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2017},
  url = {https://icml.cc/virtual/2017/poster/837},
}

@inproceedings{neurips2019_a_57854,
  title = {{A unified variance-reduced accelerated gradient method for convex optimization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/14058},
}

@inproceedings{icml2016_improved_35871,
  title = {{Improved SVRG for Non-Strongly-Convex or Sum-of-Non-Convex Objectives}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2016},
  url = {https://proceedings.mlr.press/v48/allen-zhub16.html},
}

@inproceedings{neurips2020_a_59230,
  title = {{A Catalyst Framework for Minimax Optimization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/18390},
}

@inproceedings{neurips2020_sgd_60762,
  title = {{SGD with shuffling: optimal rates without component convexity and large epoch requirements}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/17034},
}

@inproceedings{icml2018_katyusha_36768,
  title = {{Katyusha X: Simple Momentum Method for Stochastic Sum-of-Nonconvex Optimization}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/2017},
}

@inproceedings{neurips2017_breaking_56185,
  title = {{Breaking the Nonsmooth Barrier: A Scalable Parallel Method for Composite Optimization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/8804},
}

@inproceedings{icml2018_level_36822,
  title = {{Level-Set Methods for Finite-Sum Constrained Convex Optimization}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/2122},
}

@inproceedings{icml2020_lower_38437,
  title = {{Lower Complexity Bounds for Finite-Sum Convex-Concave Minimax Optimization Problems}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6431},
}

@inproceedings{neurips2020_dual_59743,
  title = {{Dual-Free Stochastic Decentralized Optimization with Variance Reduction}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/16973},
}

@inproceedings{icml2020_a_37890,
  title = {{A simpler approach to accelerated optimization: iterative averaging meets optimism}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6822},
}

@inproceedings{icml2021_a_38964,
  title = {{A Hybrid Variance-Reduced Method for Decentralized Stochastic Non-Convex Optimization}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2021},
  url = {https://icml.cc/virtual/2021/poster/8935},
}

@inproceedings{neurips2017_limitations_56450,
  title = {{Limitations on Variance-Reduction and Acceleration Schemes for Finite Sums Optimization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/9137},
}

@inproceedings{neurips2018_breaking_56927,
  title = {{Breaking the Span Assumption Yields Fast Finite-Sum Minimization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11241},
}

@inproceedings{neurips2020_variance_61071,
  title = {{Variance Reduction via Accelerated Dual Averaging for Finite-Sum Optimization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/17116},
}

@inproceedings{aaai2024_decentralized_5614,
  title = {{Decentralized Sum-of-Nonconvex Optimization}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29318},
}

@inproceedings{aaai2025_faster_9154,
  title = {{Faster Double Adaptive Gradient Methods}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/34908},
}

@inproceedings{iclr2024_efficient_34431,
  title = {{Efficient Continual Finite-Sum Minimization}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18644},
}

@inproceedings{icml2024_efficient_45406,
  title = {{Efficient Algorithms for Empirical Group Distributionally Robust Optimization and Beyond}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33045},
}

@inproceedings{icml2025_a_47728,
  title = {{A Near-Optimal Single-Loop Stochastic Algorithm for Convex Finite-Sum Coupled Compositional Optimization}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/44872},
}

@inproceedings{neurips2025_a_79654,
  title = {{A Near-Optimal Algorithm for Decentralized Convex-Concave Finite-Sum Minimax Optimization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=raZEmZ48h4},
}

@inproceedings{iclr2025_mgda_83995,
  title = {{MGDA Converges under Generalized Smoothness, Provably}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/27830},
}

@inproceedings{neurips2026_constrained_92856,
  title = {{Constrained Stochastic Spectral Preconditioning Converges for Nonconvex Objectives}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/149304},
}

@inproceedings{aaai2026_decentralized_106785,
  title = {{Decentralized Non-convex Stochastic Optimization with Heterogeneous Variance}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/39092},
}

@inproceedings{icml2024_decentralized_44153,
  title = {{Decentralized Convex Finite-Sum Optimization with Better Dependence on Condition Numbers}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34299},
}

@inproceedings{neurips2024_freya_70949,
  title = {{Freya PAGE: First Optimal Time Complexity for Large-Scale Nonconvex Finite-Sum Optimization with Heterogeneous Asynchronous Computations}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/96254},
}

@inproceedings{neurips2026_accelerated_91273,
  title = {{Accelerated last-iterate convergence of Extragradient via power-law stepsizes}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/155893},
}