% Key papers for Byzantine-robust learning (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{neurips2017_machine_56460,
  title = {{Machine Learning with Adversaries: Byzantine Tolerant Gradient Descent}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/8810},
}

@inproceedings{icml2018_byzantine_36560,
  title = {{Byzantine-Robust Distributed Learning: Towards Optimal Statistical Rates}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/2405},
}

@inproceedings{icml2018_the_37035,
  title = {{The Hidden Vulnerability of Distributed Learning in Byzantium}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/2351},
}

@inproceedings{aaai2019_rsa_100612,
  title = {{RSA: Byzantine-Robust Stochastic Aggregation Methods for Distributed Learning from Heterogeneous Datasets}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2019},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/3968},
}

@inproceedings{neurips2018_byzantine_56929,
  title = {{Byzantine Stochastic Gradient Descent}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11454},
}

@inproceedings{icml2019_zeno_37860,
  title = {{Zeno: Distributed Stochastic Gradient Descent with Suspicion-based Fault-tolerance}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/3783},
}

@inproceedings{icml2018_asynchronous_36524,
  title = {{Asynchronous Byzantine Machine Learning (the case of SGD)}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/1963},
}

@inproceedings{neurips2020_election_59779,
  title = {{Election Coding for Distributed Learning: Protecting SignSGD against Byzantine Attacks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/17515},
}

@inproceedings{iclr2021_distributed_30153,
  title = {{Distributed Momentum for Byzantine-resilient Stochastic Gradient Descent}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2021},
  url = {https://iclr.cc/virtual/2021/poster/2636},
}

@inproceedings{iclr2019_toward_28843,
  title = {{Toward Understanding the Impact of Staleness in Distributed Machine Learning}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2019},
  url = {https://iclr.cc/virtual/2019/poster/961},
}

@inproceedings{iclr2021_byzantine_30281,
  title = {{Byzantine-Resilient Non-Convex Stochastic Gradient Descent}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2021},
  url = {https://iclr.cc/virtual/2021/poster/3312},
}

@inproceedings{aaai2024_byzantine_5324,
  title = {{Byzantine-Robust Decentralized Learning via Remove-then-Clip Aggregation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/30173},
}

@inproceedings{icml2019_defending_37280,
  title = {{Defending Against Saddle Point Attack in Byzantine-Robust Distributed Learning}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/3660},
}

@inproceedings{icml2022_byzantine_40309,
  title = {{Byzantine Machine Learning Made Easy By Resilient Averaging of Momentums}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2022},
  url = {https://icml.cc/virtual/2022/poster/17605},
}

@inproceedings{aaai2022_distributed_1991,
  title = {{Distributed Learning with Strategic Users: A Repeated Game Approach}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2022},
  url = {https://aaai.org/papers/05976-distributed-learning-with-strategic-users-a-repeated-game-approach/},
}

@inproceedings{icml2021_basgd_39077,
  title = {{BASGD: Buffered Asynchronous SGD for Byzantine Learning}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2021},
  url = {https://icml.cc/virtual/2021/poster/8819},
}

@inproceedings{neurips2020_distributed_59721,
  title = {{Distributed Newton Can Communicate Less and Resist Byzantine Workers}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/18294},
}

@inproceedings{icml2023_robust_41779,
  title = {{Robust Collaborative Learning with Linear Gradient Overhead}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2023},
  url = {https://icml.cc/virtual/2023/poster/24585},
}

@inproceedings{neurips2024_weight_74327,
  title = {{Weight for Robustness: A Comprehensive Approach towards Optimal Fault-Tolerant Asynchronous ML}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93233},
}

@inproceedings{icml2020_zeno_38946,
  title = {{Zeno++: Robust Fully Asynchronous SGD}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6052},
}

@inproceedings{icml2024_fault_44009,
  title = {{Fault Tolerant ML: Efficient Meta-Aggregation and Synchronous Training}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34443},
}

@inproceedings{icml2024_dynamic_44268,
  title = {{Dynamic Byzantine-Robust Learning: Adapting to Switching Byzantine Workers}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34184},
}

@inproceedings{icml2026_improving_52949,
  title = {{Improving the Robustness-Utility Trade-off in Decentralized Learning over Sparse Networks}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=aYUmbbRVbJ},
}

@inproceedings{iclr2025_adaptive_80490,
  title = {{Adaptive Gradient Clipping for Robust Federated Learning}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/31272},
}

@inproceedings{neurips2026_from_90346,
  title = {{From Inexact Gradients to Byzantine Robustness: Acceleration and Optimization under Similarity}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/148563},
}

@inproceedings{neurips2026_adversary_90414,
  title = {{Adversary-Robust Learning from Fully Asynchronous Directional Derivative Estimates}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/154942},
}

@inproceedings{neurips2026_resist_92606,
  title = {{RESIST: Resilient Decentralized Learning Using Consensus Gradient Descent}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/156789},
}

@inproceedings{aaai2026_high_107208,
  title = {{High Dimensional Distributed Gradient Descent with Arbitrary Number of Byzantine Attackers}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/39560},
}

@inproceedings{iclr2024_on_35597,
  title = {{On the Effect of Batch Size in Byzantine-Robust Distributed Learning}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/17476},
}

@inproceedings{icml2025_byzantine_48242,
  title = {{Byzantine-Resilient Federated Alternating Gradient Descent and Minimization for Partly-Decoupled Low Rank Matrix Learning}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/44370},
}

@inproceedings{icml2025_on_49148,
  title = {{On the Tension between Byzantine Robustness and No-Attack Accuracy in Distributed Learning}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/43477},
}