% Key papers for Decentralized optimization algorithms (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{icml2017_optimal_36329,
  title = {{Optimal Algorithms for Smooth and Strongly Convex Distributed Optimization in Networks}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2017},
  url = {https://icml.cc/virtual/2017/poster/685},
}

@inproceedings{icml2020_a_37886,
  title = {{A Unified Theory of Decentralized SGD with Changing Topology and Local Updates}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6533},
}

@inproceedings{neurips2017_straggler_56693,
  title = {{Straggler Mitigation in Distributed Optimization Through Data Encoding}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/9318},
}

@inproceedings{neurips2018_optimal_57482,
  title = {{Optimal Algorithms for Non-Smooth Distributed Optimization in Networks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11281},
}

@inproceedings{cvpr2016_a_11356,
  title = {{A Consensus-Based Framework for Distributed Bundle Adjustment}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2016},
}

@inproceedings{aaai2016_fast_104810,
  title = {{Fast ADMM Algorithm for Distributed Optimization with Adaptive Penalty}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2016},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/10069},
}

@inproceedings{neurips2018_decentralize_56996,
  title = {{Decentralize and Randomize: Faster Algorithm for Wasserstein Barycenters}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/12017},
}

@inproceedings{icml2017_efficient_36169,
  title = {{Efficient Distributed Learning with Sparsity}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2017},
  url = {https://icml.cc/virtual/2017/poster/584},
}

@inproceedings{icml2019_on_37600,
  title = {{On the Complexity of Approximating Wasserstein Barycenters}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/4071},
}

@inproceedings{icml2017_adaptive_36050,
  title = {{Adaptive Consensus ADMM for Distributed Optimization}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2017},
  url = {https://icml.cc/virtual/2017/poster/632},
}

@inproceedings{icml2020_improving_38311,
  title = {{Improving the Sample and Communication Complexity for Decentralized Non-Convex Optimization: Joint Gradient Estimation and Tracking}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6030},
}

@inproceedings{icml2020_quantized_38662,
  title = {{Quantized Decentralized Stochastic Learning over Directed Graphs}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6342},
}

@inproceedings{neurips2019_dingo_58079,
  title = {{DINGO: Distributed Newton-Type Method for Gradient-Norm Optimization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13986},
}

@inproceedings{neurips2018_giant_57149,
  title = {{GIANT: Globally Improved Approximate Newton Method for Distributed Optimization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11243},
}

@inproceedings{icml2016_gossip_35855,
  title = {{Gossip Dual Averaging for Decentralized Optimization of Pairwise Functions}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2016},
  url = {https://proceedings.mlr.press/v48/colin16.html},
}

@inproceedings{neurips2019_an_57892,
  title = {{An Accelerated Decentralized Stochastic Proximal Algorithm for Finite Sums}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13324},
}

@inproceedings{iclr2019_anytime_29197,
  title = {{ANYTIME MINIBATCH: EXPLOITING STRAGGLERS IN ONLINE DISTRIBUTED OPTIMIZATION}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2019},
  url = {https://iclr.cc/virtual/2019/poster/970},
}

@inproceedings{icml2018_a_36470,
  title = {{A Delay-tolerant Proximal-Gradient Algorithm for Distributed Learning}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/2143},
}

@inproceedings{neurips2020_distributionally_59727,
  title = {{Distributionally Robust Federated Averaging}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/18195},
}

@inproceedings{icml2018_asynchronous_36526,
  title = {{Asynchronous Stochastic Quasi-Newton MCMC for Non-Convex Optimization}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/1877},
}

@inproceedings{aaai2024_jointly_6364,
  title = {{Jointly Improving the Sample and Communication Complexities in Decentralized Stochastic Minimax Optimization}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/30076},
}

@inproceedings{icml2024_high_43812,
  title = {{High-Probability Convergence for Composite and Distributed Stochastic Minimization and Variational Inequalities with Heavy-Tailed Noise}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34640},
}

@inproceedings{iclr2024_communication_34976,
  title = {{Communication-Efficient Gradient Descent-Accent Methods for Distributed Variational Inequalities: Unified Analysis and Local Updates}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18098},
}

@inproceedings{aaai2024_communication_5434,
  title = {{Communication Efficient Distributed Newton Method over Unreliable Networks}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29513},
}

@inproceedings{neurips2024_b_70346,
  title = {{B-ary Tree Push-Pull Method is Provably Efficient for Distributed Learning on Heterogeneous Data}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/96751},
}

@inproceedings{neurips2024_stabilized_72564,
  title = {{Stabilized Proximal-Point Methods for Federated Optimization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94808},
}

@inproceedings{neurips2024_near_73978,
  title = {{Near-Optimal Distributed Minimax Optimization under the Second-Order Similarity}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93537},
}

@inproceedings{aaai2025_hybrid_9468,
  title = {{Hybrid Decentralized Optimization: Leveraging Both First- and Zeroth-Order Optimizers for Faster Convergence}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/34290},
}

@inproceedings{icml2025_riemannian_46157,
  title = {{Riemannian Diffusion Adaptation for Distributed Optimization on Manifolds}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/46403},
}

@inproceedings{icml2025_exploiting_47427,
  title = {{Exploiting Similarity for Computation and Communication-Efficient Decentralized Optimization}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/45166},
}

@inproceedings{icml2025_distributed_48677,
  title = {{Distributed Event-Based Learning via ADMM}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/43945},
}

@inproceedings{icml2026_fab_53169,
  title = {{FAB: A First-Order AB-based Gradient Algorithm for Distributed Bilevel Optimization over Time-Varying Directed Graphs}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=coINrhVRkL},
}

@inproceedings{neurips2024_slowcalsgd_70987,
  title = {{SLowcalSGD : Slow Query Points Improve Local-SGD for Stochastic Convex Optimization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/96219},
}

@inproceedings{neurips2024_on_71497,
  title = {{On the Optimal Time Complexities in Decentralized Stochastic Asynchronous Optimization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95763},
}

@inproceedings{iclr2025_newton_82292,
  title = {{Newton Meets Marchenko-Pastur: Massively Parallel Second-Order Optimization with Hessian Sketching and Debiasing}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/29499},
}

@inproceedings{iclr2025_convergence_82376,
  title = {{Convergence of Distributed Adaptive Optimization with Local Updates}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/29416},
}

@inproceedings{iclr2026_proving_84219,
  title = {{Proving the Limited Scalability of Centralized Distributed Optimization via a New Lower Bound Construction}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=0KXI6lDM9C},
}

@inproceedings{iclr2026_communication_85725,
  title = {{Communication-Efficient Decentralized Optimization via Double-Communication Symmetric ADMM}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=HZYuyNkBdD},
}

@inproceedings{neurips2026_faster_89940,
  title = {{Faster Rates For Federated Variational Inequalities}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/152615},
}

@inproceedings{neurips2026_stochastic_90043,
  title = {{Stochastic Matching via Local Sparsification}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/150334},
}