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

@inproceedings{neurips2020_personalized_60579,
  title = {{Personalized Federated Learning with Moreau Envelopes}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/18227},
}

@inproceedings{iclr2021_adaptive_30210,
  title = {{Adaptive Federated Optimization}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2021},
  url = {https://iclr.cc/virtual/2021/poster/2691},
}

@inproceedings{aaai2021_game_653,
  title = {{Game of Gradients: Mitigating Irrelevant Clients in Federated Learning}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/09046-game-of-gradients-mitigating-irrelevant-clients-in-federated-learning/},
}

@inproceedings{cvpr2023_elastic_20908,
  title = {{Elastic Aggregation for Federated Optimization}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2023},
  url = {https://cvpr.thecvf.com/virtual/2023/poster/20950},
}

@inproceedings{neurips2022_fedavg_64428,
  title = {{FedAvg with Fine Tuning: Local Updates Lead to Representation Learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/54190},
}

@inproceedings{aaai2024_efficient_5801,
  title = {{Efficient Asynchronous Federated Learning with Prospective Momentum Aggregation and Fine-Grained Correction}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29603},
}

@inproceedings{cvpr2024_decentralized_23120,
  title = {{Decentralized Directed Collaboration for Personalized Federated Learning}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/30232},
}

@inproceedings{neurips2021_fast_61220,
  title = {{Fast Federated Learning in the Presence of Arbitrary Device Unavailability}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/27665},
}

@inproceedings{aaai2022_coordinating_1892,
  title = {{Coordinating Momenta for Cross-Silo Federated Learning}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2022},
  url = {https://aaai.org/papers/08735-coordinating-momenta-for-cross-silo-federated-learning/},
}

@inproceedings{icml2022_communication_40342,
  title = {{Communication-Efficient Adaptive Federated Learning}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2022},
  url = {https://icml.cc/virtual/2022/poster/18273},
}

@inproceedings{neurips2021_stem_61876,
  title = {{STEM: A Stochastic Two-Sided Momentum Algorithm Achieving Near-Optimal Sample and Communication Complexities for Federated Learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/27176},
}

@inproceedings{iclr2022_acceleration_30862,
  title = {{Acceleration of Federated Learning with Alleviated Forgetting in Local Training}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2022},
  url = {https://iclr.cc/virtual/2022/poster/6422},
}

@inproceedings{neurips2024_convergence_74296,
  title = {{Convergence Analysis of Split Federated Learning on Heterogeneous Data}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93262},
}

@inproceedings{iclr2021_achieving_30561,
  title = {{Achieving Linear Speedup with Partial Worker Participation in Non-IID Federated Learning}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2021},
  url = {https://iclr.cc/virtual/2021/poster/2729},
}

@inproceedings{icml2021_federated_39346,
  title = {{Federated Learning under Arbitrary Communication Patterns}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2021},
  url = {https://icml.cc/virtual/2021/poster/9203},
}

@inproceedings{icml2022_accelerated_40197,
  title = {{Accelerated Federated Learning with Decoupled Adaptive Optimization}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2022},
  url = {https://icml.cc/virtual/2022/poster/17539},
}

@inproceedings{aaai2024_z_7856,
  title = {{z-SignFedAvg: A Unified Stochastic Sign-Based Compression for Federated Learning}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29454},
}

@inproceedings{iclr2023_fedspeed_32849,
  title = {{FedSpeed: Larger Local Interval, Less Communication Round, and Higher Generalization Accuracy}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2023},
  url = {https://iclr.cc/virtual/2023/poster/11870},
}

@inproceedings{neurips2022_fairness_65846,
  title = {{Fairness in Federated Learning via Core-Stability}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/52828},
}

@inproceedings{neurips2024_hierarchical_72822,
  title = {{Hierarchical Federated Learning with Multi-Timescale Gradient Correction}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94577},
}

@inproceedings{neurips2024_a_73347,
  title = {{A-FedPD: Aligning Dual-Drift is All Federated Primal-Dual Learning Needs}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94099},
}

@inproceedings{iclr2024_adaptive_34912,
  title = {{Adaptive Federated Learning with Auto-Tuned Clients}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18162},
}

@inproceedings{aaai2024_algorithmic_5157,
  title = {{Algorithmic Foundation of Federated Learning with Sequential Data}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/30291},
}

@inproceedings{iclr2024_momentum_34509,
  title = {{Momentum Benefits Non-iid Federated Learning Simply and Provably}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18565},
}

@inproceedings{icml2024_fadas_45125,
  title = {{FADAS: Towards Federated Adaptive Asynchronous Optimization}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33327},
}

@inproceedings{aaai2025_creating_8557,
  title = {{Creating Coherence in Federated Non-Negative Matrix Factorization}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/33772},
}

@inproceedings{aaai2025_first_9202,
  title = {{First-Order Federated Bilevel Learning}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/34355},
}

@inproceedings{aaai2025_lid_9786,
  title = {{LiD-FL: Towards List-Decodable Federated Learning}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/34072},
}

@inproceedings{icml2024_federated_44061,
  title = {{Federated Optimization with Doubly Regularized Drift Correction}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34391},
}

@inproceedings{icml2025_generalization_48358,
  title = {{Generalization in Federated Learning: A Conditional Mutual Information Framework}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/44258},
}

@inproceedings{icml2026_federated_49952,
  title = {{Federated Bilevel Performative Prediction}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=7XUocfk7eQ},
}

@inproceedings{neurips2025_multiplayer_75548,
  title = {{Multiplayer Federated Learning: Reaching Equilibrium with Less Communication}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=9JX8XrTVEz},
}

@inproceedings{neurips2025_fedqs_78155,
  title = {{FedQS: Optimizing Gradient and Model Aggregation for Semi-Asynchronous Federated Learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=bbVB4ZaqEf},
}

@inproceedings{neurips2025_streaming_78880,
  title = {{Streaming Federated Learning with Markovian Data}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=jIJhQ51NxO},
}

@inproceedings{iclr2025_debiasing_81095,
  title = {{Debiasing Federated Learning with Correlated Client Participation}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/30673},
}