% Key papers for Coordinate and Adam convergence analysis (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{iclr2018_on_28414,
  title = {{On the regularization of Wasserstein GANs}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2018},
  url = {https://iclr.cc/virtual/2018/poster/17},
}

@inproceedings{icml2017_variants_36447,
  title = {{Variants of RMSProp and Adagrad with Logarithmic Regret Bounds}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2017},
  url = {https://icml.cc/virtual/2017/poster/884},
}

@inproceedings{aaai2018_finite_106058,
  title = {{Finite Sample Analyses for TD(0) With Function Approximation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2018},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/12079},
}

@inproceedings{icml2019_plug_37655,
  title = {{Plug-and-Play Methods Provably Converge with Properly Trained Denoisers}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/4180},
}

@inproceedings{neurips2016_stochastic_56013,
  title = {{Stochastic Online AUC Maximization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2016},
  url = {https://nips.cc/virtual/2016/poster/7408},
}

@inproceedings{iclr2019_on_28883,
  title = {{On the Convergence of A Class of Adam-Type Algorithms for Non-Convex Optimization}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2019},
  url = {https://iclr.cc/virtual/2019/poster/774},
}

@inproceedings{iclr2020_why_29297,
  title = {{Why Gradient Clipping Accelerates Training: A Theoretical Justification for Adaptivity}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2020},
  url = {https://openreview.net/forum?id=BJgnXpVYwS},
}

@inproceedings{iclr2020_neural_29292,
  title = {{Neural Policy Gradient Methods: Global Optimality and Rates of Convergence}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2020},
  url = {https://openreview.net/forum?id=BJgQfkSYDS},
}

@inproceedings{icml2020_on_38552,
  title = {{On the Global Convergence Rates of Softmax Policy Gradient Methods}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6712},
}

@inproceedings{iclr2019_proxquant_28994,
  title = {{ProxQuant: Quantized Neural Networks via Proximal Operators}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2019},
  url = {https://iclr.cc/virtual/2019/poster/828},
}

@inproceedings{neurips2020_natural_60382,
  title = {{Natural Policy Gradient Primal-Dual Method for Constrained Markov Decision Processes}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/18416},
}

@inproceedings{neurips2019_finite_58279,
  title = {{Finite-Sample Analysis for SARSA with Linear Function Approximation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13923},
}

@inproceedings{aaai2019_robust_101685,
  title = {{Robust Optimization over Multiple Domains}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2019},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/4400},
}

@inproceedings{neurips2017_convergent_56219,
  title = {{Convergent Block Coordinate Descent for Training Tikhonov Regularized Deep Neural Networks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/8962},
}

@inproceedings{neurips2019_two_59126,
  title = {{Two Time-scale Off-Policy TD Learning: Non-asymptotic Analysis over Markovian Samples}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/14070},
}

@inproceedings{neurips2016_learning_55826,
  title = {{Learning Supervised PageRank with Gradient-Based and Gradient-Free Optimization Methods}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2016},
  url = {https://nips.cc/virtual/2016/poster/8507},
}

@inproceedings{icml2020_coresets_38061,
  title = {{Coresets for Data-efficient Training of Machine Learning Models}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6325},
}

@inproceedings{iclr2020_stochastic_29449,
  title = {{Stochastic AUC Maximization with Deep Neural Networks}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2020},
  url = {https://openreview.net/forum?id=HJepXaVYDr},
}

@inproceedings{aaai2020_a_101919,
  title = {{A Tale of Two-Timescale Reinforcement Learning with the Tightest Finite-Time Bound}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2020},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/5779},
}

@inproceedings{icml2019_global_37401,
  title = {{Global Convergence of Block Coordinate Descent in Deep Learning}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/3715},
}

@inproceedings{aaai2024_ppo_6904,
  title = {{PPO-Clip Attains Global Optimality: Towards Deeper Understandings of Clipping}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29154},
}

@inproceedings{neurips2024_adam_74330,
  title = {{Adam with model exponential moving average is effective for nonconvex optimization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93230},
}

@inproceedings{aaai2024_provably_7022,
  title = {{Provably Convergent Federated Trilevel Learning}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29190},
}

@inproceedings{icml2024_accelerating_44100,
  title = {{Accelerating Convergence of Score-Based Diffusion Models, Provably}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34352},
}

@inproceedings{neurips2024_on_71529,
  title = {{On the Stability and Generalization of Meta-Learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95734},
}

@inproceedings{neurips2024_fundamental_72042,
  title = {{Fundamental Convergence Analysis of Sharpness-Aware Minimization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95276},
}

@inproceedings{aaai2025_stability_10830,
  title = {{Stability and Generalization of Zeroth-Order Decentralized Stochastic Gradient Descent with Changing Topology}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/33906},
}

@inproceedings{icml2024_compact_44298,
  title = {{Compact Optimality Verification for Optimization Proxies}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34154},
}

@inproceedings{neurips2024_the_71307,
  title = {{The Power of Extrapolation in Federated Learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95940},
}

@inproceedings{neurips2024_mirror_71829,
  title = {{Mirror and Preconditioned Gradient Descent in Wasserstein Space}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95469},
}

@inproceedings{neurips2024_gradient_72435,
  title = {{Gradient-Variation Online Learning under Generalized Smoothness}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94921},
}

@inproceedings{neurips2024_deep_73257,
  title = {{Deep Learning for Computing Convergence Rates of Markov Chains}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94182},
}

@inproceedings{neurips2025_gradient_79187,
  title = {{Gradient-Variation Online Adaptivity for Accelerated Optimization with Hölder Smoothness}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=miYvfEKvEl},
}

@inproceedings{aaai2025_on_10174,
  title = {{On the Convergence of Tâtonnement for Linear Fisher Markets}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/33535},
}

@inproceedings{aaai2025_stability_10831,
  title = {{Stability-based Generalization Analysis of Randomized Coordinate Descent for Pairwise Learning}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/35457},
}

@inproceedings{iclr2024_pilot_34345,
  title = {{PILOT: An \$mathcalO(1/K)\$-Convergent Approach for Policy Evaluation with Nonlinear Function Approximation}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18730},
}

@inproceedings{icml2024_convergence_43776,
  title = {{Convergence of Some Convex Message Passing Algorithms to a Fixed Point}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34676},
}

@inproceedings{icml2024_efficient_45170,
  title = {{Efficient Algorithms for Sum-Of-Minimum Optimization}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33282},
}

@inproceedings{icml2025_convergence_46320,
  title = {{Convergence of Policy Mirror Descent Beyond Compatible Function Approximation}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/46241},
}

@inproceedings{icml2025_armijo_46985,
  title = {{Armijo Line-search Can Make (Stochastic) Gradient Descent Provably Faster}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/45597},
}