% Key papers for Optimal mean estimation and subsampling (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{neurips2016_global_55756,
  title = {{Global Analysis of Expectation Maximization for Mixtures of Two Gaussians}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2016},
  url = {https://nips.cc/virtual/2016/poster/7216},
}

@inproceedings{iclr2020_maxmin_29339,
  title = {{Maxmin Q-learning: Controlling the Estimation Bias of Q-learning}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2020},
  url = {https://openreview.net/forum?id=Bkg0u3Etwr},
}

@inproceedings{icml2016_estimating_35821,
  title = {{Estimating Maximum Expected Value through Gaussian Approximation}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2016},
  url = {https://proceedings.mlr.press/v48/deramo16.html},
}

@inproceedings{aaai2019_the_100198,
  title = {{The Kelly Growth Optimal Portfolio with Ensemble Learning}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2019},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/3906},
}

@inproceedings{aaai2020_on_101060,
  title = {{On Performance Estimation in Automatic Algorithm Configuration}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2020},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/5618},
}

@inproceedings{icml2016_truthful_36019,
  title = {{Truthful Univariate Estimators}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2016},
  url = {https://proceedings.mlr.press/v48/caragiannis16.html},
}

@inproceedings{neurips2016_interpretable_55795,
  title = {{Interpretable Distribution Features with Maximum Testing Power}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2016},
  url = {https://nips.cc/virtual/2016/poster/7425},
}

@inproceedings{icml2019_distributed_37302,
  title = {{Distributed Learning with Sublinear Communication}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/3787},
}

@inproceedings{icml2020_logistic_38428,
  title = {{Logistic Regression for Massive Data with Rare Events}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6536},
}

@inproceedings{neurips2016_an_55577,
  title = {{An equivalence between high dimensional Bayes optimal inference and M-estimation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2016},
  url = {https://nips.cc/virtual/2016/poster/7203},
}

@inproceedings{neurips2021_nonuniform_63417,
  title = {{Nonuniform Negative Sampling and Log Odds Correction with Rare Events Data}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/28471},
}

@inproceedings{neurips2016_estimating_55713,
  title = {{Estimating the Size of a Large Network and its Communities from a Random Sample}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2016},
  url = {https://nips.cc/virtual/2016/poster/7364},
}

@inproceedings{aaai2019_interpretable_100588,
  title = {{Interpretable Predictive Modeling for Climate Variables with Weighted Lasso}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2019},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/3939},
}

@inproceedings{icml2017_high_36217,
  title = {{High-Dimensional Structured Quantile Regression}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2017},
  url = {https://icml.cc/virtual/2017/poster/741},
}

@inproceedings{neurips2017_the_56724,
  title = {{The power of absolute discounting: all-dimensional distribution estimation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/9434},
}

@inproceedings{neurips2021_a_63247,
  title = {{A Theory of the Distortion-Perception Tradeoff in Wasserstein Space}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/28035},
}

@inproceedings{icml2020_data_38073,
  title = {{Data Amplification: Instance-Optimal Property Estimation}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2020},
  url = {https://icml.cc/virtual/2020/poster/6805},
}

@inproceedings{neurips2022_k_64637,
  title = {{\$k\$-Sliced Mutual Information: A Quantitative Study of Scalability with Dimension}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/52868},
}

@inproceedings{aaai2019_bias_101655,
  title = {{Bias-Variance Trade-Off in Hierarchical Probabilistic Models Using Higher-Order Feature Interactions}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2019},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/4362},
}

@inproceedings{icml2017_estimating_36181,
  title = {{Estimating the unseen from multiple populations}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2017},
  url = {https://icml.cc/virtual/2017/poster/885},
}

@inproceedings{neurips2024_sigmoid_71480,
  title = {{Sigmoid Gating is More Sample Efficient than Softmax Gating in Mixture of Experts}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95780},
}

@inproceedings{aaai2024_testing_7526,
  title = {{Testing Self-Reducible Samplers}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/28632},
}

@inproceedings{iclr2024_maximum_34868,
  title = {{Maximum Likelihood Estimation is All You Need for Well-Specified Covariate Shift}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18206},
}

@inproceedings{iclr2024_statistical_35073,
  title = {{Statistical Perspective of Top-K Sparse Softmax Gating Mixture of Experts}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18000},
}

@inproceedings{neurips2024_data_70192,
  title = {{Data Distribution Valuation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/96892},
}

@inproceedings{aaai2025_from_9250,
  title = {{From Understanding Genetic Drift to a Smart-Restart Mechanism for Estimation-of-Distribution Algorithms (Journal Track)}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/35137},
}

@inproceedings{icml2024_on_43724,
  title = {{On Least Square Estimation in Softmax Gating Mixture of Experts}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34728},
}

@inproceedings{icml2024_agnostic_44973,
  title = {{Agnostic Learning of Mixed Linear Regressions with EM and AM Algorithms}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33479},
}

@inproceedings{icml2026_sobolev_53364,
  title = {{Sobolev Regularized Score Difference Estimation in Diffusion Models}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=en3Ws2v1Ts},
}

@inproceedings{neurips2024_variance_71457,
  title = {{Variance estimation in compound decision theory under boundedness}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95799},
}

@inproceedings{neurips2025_on_75610,
  title = {{On the Optimality of the Median-of-Means Estimator under Adversarial Contamination}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=A0aUS60Kvk},
}

@inproceedings{neurips2025_small_77636,
  title = {{Small Resamples, Sharp Guarantees: Convergence Rates for Resampled Studentized Quantile Estimators}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=VwjHVS4zZN},
}

@inproceedings{neurips2025_risk_77693,
  title = {{Risk Bounds For Distributional Regression}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=Wav9TP5SOR},
}

@inproceedings{neurips2025_tight_79453,
  title = {{Tight Asymptotics of Extreme Order Statistics}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=padrqCRyCP},
}

@inproceedings{iclr2025_how_83865,
  title = {{How Much is Unseen Depends Chiefly on Information About the Seen}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/27955},
}

@inproceedings{neurips2026_instance_90787,
  title = {{Instance-Optimal Estimation with Multiple LLM Judges on a Budget}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/149650},
}

@inproceedings{neurips2026_optimal_90930,
  title = {{Optimal sequential tests yield log-optimal e-processes}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/148381},
}

@inproceedings{neurips2026_bayes_94525,
  title = {{Bayes-Optimal BER and AUC: Estimation and Evaluation of Estimators}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/152377},
}

@inproceedings{neurips2026_ransac_95394,
  title = {{RANSAC Scoring Done Right}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/154742},
}

@inproceedings{icml2025_pairwise_46325,
  title = {{Pairwise Maximum Likelihood For Multi-Class Logistic Regression Model With Multiple Rare Classes}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/46236},
}