% Key papers for Generalization and limits under data constraints (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{iclr2018_do_28435,
  title = {{Do GANs learn the distribution? Some Theory and Empirics}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2018},
  url = {https://iclr.cc/virtual/2018/poster/72},
}

@inproceedings{aaai2018_timers_100335,
  title = {{TIMERS: Error-Bounded SVD Restart on Dynamic Networks}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2018},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/11299},
}

@inproceedings{neurips2018_the_57695,
  title = {{The Price of Fair PCA: One Extra dimension}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/12037},
}

@inproceedings{neurips2017_information_56386,
  title = {{Information Theoretic Properties of Markov Random Fields, and their Algorithmic Applications}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/9033},
}

@inproceedings{neurips2019_wasserstein_59191,
  title = {{Wasserstein Dependency Measure for Representation Learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/14450},
}

@inproceedings{icml2018_spatio_36993,
  title = {{Spatio-temporal Bayesian On-line Changepoint Detection with Model Selection}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2018},
  url = {https://icml.cc/virtual/2018/poster/1887},
}

@inproceedings{icml2016_provable_35958,
  title = {{Provable Algorithms for Inference in Topic Models}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2016},
  url = {https://proceedings.mlr.press/v48/arorab16.html},
}

@inproceedings{neurips2018_fully_57148,
  title = {{Fully Understanding The Hashing Trick}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11526},
}

@inproceedings{iclr2018_simulated_28618,
  title = {{Simulated+Unsupervised Learning With Adaptive Data Generation and Bidirectional Mappings}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2018},
  url = {https://iclr.cc/virtual/2018/poster/38},
}

@inproceedings{aaai2017_learning_104514,
  title = {{Learning Residual Alternating Automata}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2017},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/10891},
}

@inproceedings{iclr2020_learning_29566,
  title = {{Learning-Augmented Data Stream Algorithms}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2020},
  url = {https://openreview.net/forum?id=HyxJ1xBYDH},
}

@inproceedings{neurips2016_on_55908,
  title = {{On the Recursive Teaching Dimension of VC Classes}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2016},
  url = {https://nips.cc/virtual/2016/poster/7332},
}

@inproceedings{neurips2016_the_56038,
  title = {{The Limits of Learning with Missing Data}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2016},
  url = {https://nips.cc/virtual/2016/poster/6945},
}

@inproceedings{aaai2022_learning_2315,
  title = {{Learning Bayesian Networks in the Presence of Structural Side Information}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2022},
  url = {https://aaai.org/papers/07814-learning-bayesian-networks-in-the-presence-of-structural-side-information/},
}

@inproceedings{neurips2024_the_74169,
  title = {{The Impact of Initialization on LoRA Finetuning Dynamics}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93375},
}

@inproceedings{icml2020_composable_38026,
  title = {{Composable Sketches for Functions of Frequencies: Beyond the Worst Case}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6124},
}

@inproceedings{icml2020_recovery_38681,
  title = {{Recovery of Sparse Signals from a Mixture of Linear Samples}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6787},
}

@inproceedings{icml2022_understanding_41301,
  title = {{Understanding Dataset Difficulty with \$mathcalV\$-Usable Information}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2022},
  url = {https://icml.cc/virtual/2022/poster/16633},
}

@inproceedings{neurips2023_bypass_68619,
  title = {{Bypass Exponential Time Preprocessing: Fast Neural Network Training via Weight-Data Correlation Preprocessing}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2023},
  url = {https://nips.cc/virtual/2023/poster/71217},
}

@inproceedings{icml2021_rate_39855,
  title = {{Rate-Distortion Analysis of Minimum Excess Risk in Bayesian Learning}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2021},
  url = {https://icml.cc/virtual/2021/poster/9217},
}

@inproceedings{aaai2025_forecasting_9217,
  title = {{Forecasting Competitions with Correlated Events}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/33517},
}

@inproceedings{iclr2024_error_33913,
  title = {{Error Feedback Reloaded: From Quadratic to Arithmetic Mean of Smoothness Constants}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/19162},
}

@inproceedings{icml2024_unmasking_45156,
  title = {{Unmasking Vulnerabilities: Cardinality Sketches under Adaptive Inputs}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33296},
}

@inproceedings{icml2024_on_45557,
  title = {{On a Combinatorial Problem Arising in Machine Teaching}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/32895},
}

@inproceedings{icml2025_mechanisms_47250,
  title = {{Mechanisms of Projective Composition of Diffusion Models}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/45339},
}

@inproceedings{icml2026_how_51692,
  title = {{How High is ‘High’? Rethinking the Roles of Dimensionality in Topological Data Analysis and Manifold Learning}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=OtczOgWFGh},
}

@inproceedings{neurips2024_resolving_70462,
  title = {{Resolving Discrepancies in Compute-Optimal Scaling of Language Models}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/96646},
}

@inproceedings{neurips2024_universal_70607,
  title = {{Universal Rates of Empirical Risk Minimization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/96512},
}

@inproceedings{icml2024_probabilistic_43889,
  title = {{Probabilistic Generating Circuits - Demystified}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34563},
}

@inproceedings{icml2024_i_44220,
  title = {{I/O Complexity of Attention, or How Optimal is FlashAttention?}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34232},
}

@inproceedings{icml2025_representative_46466,
  title = {{Representative Language Generation}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/46100},
}

@inproceedings{icml2025_runtime_47875,
  title = {{Runtime Analysis of Evolutionary NAS for Multiclass Classification}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/44728},
}

@inproceedings{icml2025_generation_48585,
  title = {{Generation from Noisy Examples}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/44036},
}

@inproceedings{icml2026_decision_50453,
  title = {{Decision Tree Learning on Product Spaces}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=CWDsuIlJz8},
}

@inproceedings{icml2026_logit_52761,
  title = {{Logit Distance Bounds Representational Similarity}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=Yp5QTlSJJl},
}

@inproceedings{icml2026_on_53167,
  title = {{On the Learnability of Test-Time Adaptation: A Recovery Complexity Perspective}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=cnJvwUqEyu},
}

@inproceedings{icml2026_tightening_55185,
  title = {{Tightening the Score Matching Gap for Diffusion Models}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=wRairc60Ob},
}

@inproceedings{neurips2024_tight_70176,
  title = {{Tight Bounds for Learning RUMs from Small Slates}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/96908},
}

@inproceedings{neurips2024_distribution_71660,
  title = {{Distribution Learning with Valid Outputs Beyond the Worst-Case}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95620},
}