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

@inproceedings{cvpr2019_magsac_14485,
  title = {{MAGSAC: Marginalizing Sample Consensus}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2019},
}

@inproceedings{neurips2017_positive_56580,
  title = {{Positive-Unlabeled Learning with Non-Negative Risk Estimator}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/8958},
}

@inproceedings{aaai2020_stable_102014,
  title = {{Stable Prediction with Model Misspecification and Agnostic Distribution Shift}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2020},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/5876},
}

@inproceedings{iclr2020_distributionally_29907,
  title = {{Distributionally Robust Neural Networks}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2020},
  url = {https://openreview.net/forum?id=ryxGuJrFvS},
}

@inproceedings{iclr2021_the_30093,
  title = {{The Risks of Invariant Risk Minimization}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2021},
  url = {https://iclr.cc/virtual/2021/poster/2752},
}

@inproceedings{neurips2020_large_60141,
  title = {{Large-Scale Methods for Distributionally Robust Optimization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/18157},
}

@inproceedings{neurips2017_consistent_56210,
  title = {{Consistent Robust Regression}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/8999},
}

@inproceedings{cvpr2017_noise_12490,
  title = {{Noise-Blind Image Deblurring}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2017},
}

@inproceedings{icml2016_minding_35904,
  title = {{Minding the Gaps for Block Frank-Wolfe Optimization of Structured SVMs}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2016},
  url = {https://proceedings.mlr.press/v48/osokin16.html},
}

@inproceedings{neurips2019_robust_58918,
  title = {{Robust Attribution Regularization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/14352},
}

@inproceedings{aaai2021_deep_390,
  title = {{Deep Portfolio Optimization via Distributional Prediction of Residual Factors}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/00213-deep-portfolio-optimization-via-distributional-prediction-of-residual-factors/},
}

@inproceedings{aaai2017_a_104456,
  title = {{A General Framework for Sparsity Regularized Feature Selection via Iteratively Reweighted Least Square Minimization}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2017},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/10833},
}

@inproceedings{aaai2017_multilinear_104494,
  title = {{Multilinear Regression for Embedded Feature Selection with Application to fMRI Analysis}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2017},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/10871},
}

@inproceedings{neurips2018_wasserstein_57774,
  title = {{Wasserstein Distributionally Robust Kalman Filtering}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11810},
}

@inproceedings{aaai2017_portfolio_105686,
  title = {{Portfolio Selection via Subset Resampling}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2017},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/10728},
}

@inproceedings{neurips2017_on_56526,
  title = {{On Optimal Generalizability in Parametric Learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2017},
  url = {https://nips.cc/virtual/2017/poster/9129},
}

@inproceedings{aaai2020_outlier_101895,
  title = {{Outlier Detection Ensemble with Embedded Feature Selection}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2020},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/5755},
}

@inproceedings{neurips2019_beyond_57949,
  title = {{Beyond Confidence Regions: Tight Bayesian Ambiguity Sets for Robust MDPs}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13803},
}

@inproceedings{neurips2019_calibration_57972,
  title = {{Calibration tests in multi-class classification: A unifying framework}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/14609},
}

@inproceedings{aaai2020_distributionally_101937,
  title = {{Distributionally Robust Counterfactual Risk Minimization}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2020},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/5797},
}

@inproceedings{aaai2024_the_7544,
  title = {{The Evidence Contraction Issue in Deep Evidential Regression: Discussion and Solution}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/30172},
}

@inproceedings{aaai2024_uncertainty_7678,
  title = {{Uncertainty Regularized Evidential Regression}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29583},
}

@inproceedings{aaai2024_quantile_7042,
  title = {{Quantile-Regression-Ensemble: A Deep Learning Algorithm for Downscaling Extreme Precipitation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/30193},
}

@inproceedings{aaai2024_generalization_6115,
  title = {{Generalization Analysis of Machine Learning Algorithms via the Worst-Case Data-Generating Probability Measure}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29674},
}

@inproceedings{aaai2024_a_5058,
  title = {{A Provably Accurate Randomized Sampling Algorithm for Logistic Regression}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29042},
}

@inproceedings{neurips2024_theoretical_71790,
  title = {{Theoretical Investigations and Practical Enhancements on Tail Task Risk Minimization in Meta Learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95504},
}

@inproceedings{aaai2025_transfer_11099,
  title = {{Transfer Learning Meets Functional Linear Regression: No Negative Transfer Under Posterior Drift}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/33907},
}

@inproceedings{icml2024_learning_45309,
  title = {{Learning the Uncertainty Sets of Linear Control Systems via Set Membership: A Non-asymptotic Analysis}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33143},
}

@inproceedings{neurips2024_learning_70269,
  title = {{Learning from Noisy Labels via Conditional Distributionally Robust Optimization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/96820},
}

@inproceedings{neurips2024_scale_70591,
  title = {{Scale-invariant Optimal Sampling for Rare-events Data and Sparse Models}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/96526},
}

@inproceedings{aaai2026_unified_106380,
  title = {{Unified Minimax Optimization Framework for Propensity Score Estimation in Debiased Recommendation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/38687},
}

@inproceedings{aaai2024_hypothesis_6243,
  title = {{Hypothesis Testing for Class-Conditional Noise Using Local Maximum Likelihood}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/30174},
}

@inproceedings{aaai2024_towards_7604,
  title = {{Towards Large Certified Radius in Randomized Smoothing Using Quasiconcave Optimization}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/30123},
}

@inproceedings{icml2024_differentiable_43991,
  title = {{Differentiable Distributionally Robust Optimization Layers}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34461},
}

@inproceedings{icml2026_minimizing_53331,
  title = {{Minimizing Upper Confidence Bounds: A Data-Driven Framework for Stochastic Programming}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=eXLcL70GXO},
}

@inproceedings{neurips2024_bayesian_70739,
  title = {{Bayesian Nonparametrics Meets Data-Driven Distributionally Robust Optimization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/96385},
}

@inproceedings{neurips2024_tolerant_71716,
  title = {{Tolerant Algorithms for Learning with Arbitrary Covariate Shift}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95570},
}

@inproceedings{neurips2024_zipper_72869,
  title = {{Zipper: Addressing Degeneracy in Algorithm-Agnostic Inference}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94534},
}

@inproceedings{neurips2025_distributionally_75176,
  title = {{Distributionally Robust Performative Optimization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=57MeabE6QU},
}

@inproceedings{neurips2025_unveiling_77743,
  title = {{Unveiling Extraneous Sampling Bias with Data Missing-Not-At-Random}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=X8x70g0SSw},
}