% Key papers for Implicit regularization of SGD (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{neurips2017_implicit_56373,
  title = {{Implicit Regularization in Matrix Factorization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/9386},
}

@inproceedings{icml2018_implicit_36744,
  title = {{Implicit Regularization in Nonconvex Statistical Estimation: Gradient Descent Converges Linearly for Phase Retrieval and Matrix Completion}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/1893},
}

@inproceedings{icml2016_generalization_35850,
  title = {{Generalization Properties and Implicit Regularization for Multiple Passes SGM}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2016},
  url = {https://proceedings.mlr.press/v48/lina16.html},
}

@inproceedings{icml2019_learning_37511,
  title = {{Learning-to-Learn Stochastic Gradient Descent with Biased Regularization}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/4116},
}

@inproceedings{iclr2021_on_30672,
  title = {{On the Origin of Implicit Regularization in Stochastic Gradient Descent}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2021},
  url = {https://iclr.cc/virtual/2021/poster/3157},
}

@inproceedings{icml2020_the_38846,
  title = {{The Implicit Regularization of Stochastic Gradient Flow for Least Squares}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6211},
}

@inproceedings{neurips2020_bad_59424,
  title = {{Bad Global Minima Exist and SGD Can Reach Them}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/19075},
}

@inproceedings{neurips2019_implicit_58394,
  title = {{Implicit Regularization for Optimal Sparse Recovery}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13480},
}

@inproceedings{iclr2019_stochastic_28904,
  title = {{Stochastic Gradient/Mirror Descent: Minimax Optimality and Implicit Regularization}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2019},
  url = {https://iclr.cc/virtual/2019/poster/688},
}

@inproceedings{neurips2018_connecting_56960,
  title = {{Connecting Optimization and Regularization Paths}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/12003},
}

@inproceedings{iclr2021_towards_30080,
  title = {{Towards Resolving the Implicit Bias of Gradient Descent for Matrix Factorization: Greedy Low-Rank Learning}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2021},
  url = {https://iclr.cc/virtual/2021/poster/3291},
}

@inproceedings{neurips2020_robust_60742,
  title = {{Robust Recovery via Implicit Bias of Discrepant Learning Rates for Double Over-parameterization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/18242},
}

@inproceedings{neurips2021_small_63288,
  title = {{Small random initialization is akin to spectral learning: Optimization and generalization guarantees for overparameterized low-rank matrix reconstruction}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/26942},
}

@inproceedings{iclr2021_when_30321,
  title = {{When does preconditioning help or hurt generalization?}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2021},
  url = {https://iclr.cc/virtual/2021/poster/3104},
}

@inproceedings{neurips2021_the_61255,
  title = {{The Implicit Bias of Minima Stability: A View from Function Space}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/27732},
}

@inproceedings{neurips2019_implicit_58396,
  title = {{Implicit Regularization of Accelerated Methods in Hilbert Spaces}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/14366},
}

@inproceedings{neurips2020_the_60960,
  title = {{The Statistical Complexity of Early-Stopped Mirror Descent}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/17894},
}

@inproceedings{iclr2022_stochastic_31408,
  title = {{Stochastic Training is Not Necessary for Generalization}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2022},
  url = {https://iclr.cc/virtual/2022/poster/6236},
}

@inproceedings{neurips2021_the_61315,
  title = {{The Benefits of Implicit Regularization from SGD in Least Squares Problems}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/26581},
}

@inproceedings{iclr2022_large_30844,
  title = {{Large Learning Rate Tames Homogeneity: Convergence and Balancing Effect}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2022},
  url = {https://iclr.cc/virtual/2022/poster/6679},
}

@inproceedings{aaai2025_convergence_8538,
  title = {{Convergence Analysis of Federated Learning Methods Using Backward Error Analysis}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/34060},
}

@inproceedings{neurips2025_controlling_78690,
  title = {{Controlling the Flow: Stability and Convergence for Stochastic Gradient Descent with Decaying Regularization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=hMZnFo0FLF},
}

@inproceedings{icml2024_achieving_45741,
  title = {{Achieving Margin Maximization Exponentially Fast via Progressive Norm Rescaling}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/32711},
}

@inproceedings{icml2025_implicit_45954,
  title = {{Implicit Regularization for Tubal Tensor Factorizations via Gradient Descent}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/46592},
}

@inproceedings{icml2025_benefits_48424,
  title = {{Benefits of Early Stopping in Gradient Descent for Overparameterized Logistic Regression}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/44193},
}

@inproceedings{icml2026_gradient_49533,
  title = {{Gradient Descent as a Perceptron Algorithm: Understanding Dynamics and Implicit Acceleration}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=3M1Nsgd9Fb},
}

@inproceedings{neurips2024_implicit_71802,
  title = {{Implicit Regularization of Decentralized Gradient Descent for Sparse Regression}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95493},
}

@inproceedings{neurips2025_optimal_79065,
  title = {{Optimal Rates in Continual Linear Regression via Increasing Regularization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=lDh78hf5Vk},
}

@inproceedings{iclr2025_convergence_81317,
  title = {{Convergence and Implicit Bias of Gradient Descent on Continual Linear Classification}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/30455},
}

@inproceedings{neurips2026_random_89952,
  title = {{Random Matrix Theory of Early-Stopped Gradient Flow: A Transient BBP Scenario}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/149949},
}

@inproceedings{neurips2026_high_90358,
  title = {{High-dimensional Limit of SGD for Diagonal Linear Networks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/155594},
}

@inproceedings{iclr2025_towards_83721,
  title = {{Towards Learning High-Precision Least Squares Algorithms with Sequence Models}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/28098},
}

@inproceedings{iclr2026_on_85265,
  title = {{ON THE ROLE OF IMPLICIT REGULARIZATION OF STOCHASTIC GRADIENT DESCENT IN GROUP ROBUSTNESS}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=CPdAB7H8mU},
}

@inproceedings{iclr2026_gradient_86637,
  title = {{Gradient Descent Dynamics of Rank-One Matrix Denoising}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=S5oAnaIbgb},
}

@inproceedings{iclr2026_gradient_89261,
  title = {{Gradient Descent with Large Step Sizes: Chaos and Fractal Convergence Region}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=wsxGCaBjWC},
}

@inproceedings{neurips2026_constrained_93843,
  title = {{Constrained Factorization with Diagonal Scaling: Rank-Revealing Training and Pruning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/152576},
}

@inproceedings{neurips2026_uniform_95128,
  title = {{Uniform Spectral Growth under Factor-wise Muon Orthogonalization in Matrix Factorization and LoRA}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/151601},
}