% Key papers for High-dimensional asymptotic generalization (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{icml2019_on_37611,
  title = {{On the Spectral Bias of Neural Networks}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/4226},
}

@inproceedings{iclr2019_meta_28992,
  title = {{Meta-learning with differentiable closed-form solvers}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2019},
  url = {https://iclr.cc/virtual/2019/poster/669},
}

@inproceedings{icml2020_generalisation_38241,
  title = {{Generalisation error in learning with random features and the hidden manifold model}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6414},
}

@inproceedings{iclr2023_what_31921,
  title = {{What learning algorithm is in-context learning? Investigations with linear models}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2023},
  url = {https://iclr.cc/virtual/2023/poster/10852},
}

@inproceedings{icml2021_provable_39823,
  title = {{Provable Meta-Learning of Linear Representations}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2021},
  url = {https://icml.cc/virtual/2021/poster/9333},
}

@inproceedings{neurips2018_learning_57299,
  title = {{Learning To Learn Around A Common Mean}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11964},
}

@inproceedings{neurips2017_hypothesis_56369,
  title = {{Hypothesis Transfer Learning via Transformation Functions}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/8853},
}

@inproceedings{neurips2018_but_56928,
  title = {{But How Does It Work in Theory? Linear SVM with Random Features}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11340},
}

@inproceedings{neurips2020_generalization_59932,
  title = {{Generalization error in high-dimensional perceptrons: Approaching Bayes error with convex optimization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/17595},
}

@inproceedings{icml2016_the_36010,
  title = {{The Teaching Dimension of Linear Learners}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2016},
  url = {https://proceedings.mlr.press/v48/liua16.html},
}

@inproceedings{neurips2020_minimax_60322,
  title = {{Minimax Lower Bounds for Transfer Learning with Linear and One-hidden Layer Neural Networks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/18890},
}

@inproceedings{neurips2020_theoretical_60969,
  title = {{Theoretical Insights Into Multiclass Classification: A High-dimensional Asymptotic View}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/17186},
}

@inproceedings{neurips2023_transformers_69318,
  title = {{Transformers as Statisticians: Provable In-Context Learning with In-Context Algorithm Selection}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2023},
  url = {https://nips.cc/virtual/2023/poster/70583},
}

@inproceedings{icml2021_on_39711,
  title = {{On the Inherent Regularization Effects of Noise Injection During Training}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2021},
  url = {https://icml.cc/virtual/2021/poster/9413},
}

@inproceedings{aaai2019_sparse_101700,
  title = {{Sparse Reject Option Classifier Using Successive Linear Programming}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2019},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/4415},
}

@inproceedings{neurips2016_greedy_55763,
  title = {{Greedy Feature Construction}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2016},
  url = {https://nips.cc/virtual/2016/poster/6968},
}

@inproceedings{icml2024_a_43665,
  title = {{A Statistical Theory of Regularization-Based Continual Learning}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34787},
}

@inproceedings{icml2020_the_38853,
  title = {{The Role of Regularization in Classification of High-dimensional Noisy Gaussian Mixture}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6492},
}

@inproceedings{icml2022_fluctuations_40580,
  title = {{Fluctuations, Bias, Variance \& Ensemble of Learners: Exact Asymptotics for Convex Losses in High-Dimension}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2022},
  url = {https://icml.cc/virtual/2022/poster/16331},
}

@inproceedings{icml2022_more_40850,
  title = {{More Than a Toy: Random Matrix Models Predict How Real-World Neural Representations Generalize}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2022},
  url = {https://icml.cc/virtual/2022/poster/18327},
}

@inproceedings{aaai2024_tmpnn_7482,
  title = {{TMPNN: High-Order Polynomial Regression Based on Taylor Map Factorization}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29168},
}

@inproceedings{icml2026_unifying_52006,
  title = {{Unifying Low Dimensional Spectra in Deep Learning}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=RwiGcN2feP},
}

@inproceedings{iclr2024_how_35538,
  title = {{How Many Pretraining Tasks Are Needed for In-Context Learning of Linear Regression?}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/17535},
}

@inproceedings{neurips2024_bayes_72141,
  title = {{Bayes-optimal learning of an extensive-width neural network from quadratically many samples}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95194},
}

@inproceedings{neurips2024_implicit_73893,
  title = {{Implicit Regularization Paths of Weighted Neural Representations}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93618},
}

@inproceedings{iclr2024_grokking_34039,
  title = {{Grokking in Linear Estimators -- A Solvable Model that Groks without Understanding}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/19036},
}

@inproceedings{icml2024_o_45404,
  title = {{O\$n\$ Learning Deep O(\$n\$)-Equivariant Hyperspheres}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33047},
}

@inproceedings{icml2025_random_48257,
  title = {{Random Feature Representation Boosting}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/44355},
}

@inproceedings{icml2026_asymptotic_49798,
  title = {{Asymptotic Theory of Iterated Empirical Risk Minimization, with Applications to Active Learning}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=5ntMrdtnTu},
}

@inproceedings{icml2026_sharp_53174,
  title = {{Sharp Concentration Bounds for Bundle-Valued Statistics on Manifolds}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=cspPnNScXa},
}

@inproceedings{icml2026_what_55409,
  title = {{What Makes a Strong Model? A Unified Spectral Analysis of Knowledge Transfer over High-dimensional Linear Regression}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=ykWN4LG9vE},
}

@inproceedings{neurips2024_on_70543,
  title = {{On the Efficiency of ERM in Feature Learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/96570},
}

@inproceedings{neurips2025_are_75458,
  title = {{Are Greedy Task Orderings Better Than Random in Continual Linear Regression?}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=8JdPqAMpi4},
}

@inproceedings{neurips2025_the_79916,
  title = {{The \$varphi\$ Curve: The Shape of Generalization through the Lens of Norm-based Capacity Control}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=uEFC25uUwU},
}

@inproceedings{iclr2025_the_82341,
  title = {{The Breakdown of Gaussian Universality in Classification of High-dimensional Linear Factor Mixtures}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/29450},
}

@inproceedings{iclr2026_scaling_86451,
  title = {{Scaling Laws and Spectra of Shallow Neural Networks in the Feature Learning Regime}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=Q3yLIIkt7z},
}

@inproceedings{iclr2026_a_87512,
  title = {{A Statistical Theory of Overfitting for Imbalanced Classification}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=cKthi6QfUr},
}

@inproceedings{iclr2026_scaling_89492,
  title = {{Scaling Laws of SignSGD in Linear Regression: When Does It Outperform SGD?}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2026},
  url = {https://openreview.net/forum?id=zVwRP0ikrx},
}

@inproceedings{neurips2026_learning_91342,
  title = {{Learning with Synthetic Data via SGD in High-Dimensional Linear Regression}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/148876},
}