
@article{zech2018variable,
  title={Variable generalization performance of a deep learning model to detect pneumonia in chest radiographs: a cross-sectional study},
  author={Zech, John R and Badgeley, Marcus A and Liu, Manway and Costa, Anthony B and Titano, Joseph J and Oermann, Eric Karl},
  journal={PLoS medicine},
  volume={15},
  number={11},
  pages={e1002683},
  year={2018},
  publisher={Public Library of Science San Francisco, CA USA}
}

@article{orbanz2010bayesian,
  title={Bayesian Nonparametric Models.},
  author={Orbanz, Peter and Teh, Yee Whye},
  journal={Encyclopedia of machine learning},
  volume={1},
  pages={81--89},
  year={2010}
}

@inproceedings{koh2021wilds,
  title={Wilds: A benchmark of in-the-wild distribution shifts},
  author={Koh, Pang Wei and Sagawa, Shiori and Marklund, Henrik and Xie, Sang Michael and Zhang, Marvin and Balsubramani, Akshay and Hu, Weihua and Yasunaga, Michihiro and Phillips, Richard Lanas and Gao, Irena and others},
  booktitle={International Conference on Machine Learning},
  pages={5637--5664},
  year={2021},
  organization={PMLR}
}


@book{quinonero2008dataset,
  title={Dataset shift in machine learning},
  author={Quinonero-Candela, Joaquin and Sugiyama, Masashi and Schwaighofer, Anton and Lawrence, Neil D},
  year={2008},
  publisher={Mit Press}
}

@inproceedings{subbaswamy2021evaluating,
  title={Evaluating model robustness and stability to dataset shift},
  author={Subbaswamy, Adarsh and Adams, Roy and Saria, Suchi},
  booktitle={International conference on artificial intelligence and statistics},
  pages={2611--2619},
  year={2021},
  organization={PMLR}
}

@article{li2021evaluating,
  title={Evaluating model performance under worst-case subpopulations},
  author={Li, Mike and Namkoong, Hongseok and Xia, Shangzhou},
  journal={Advances in Neural Information Processing Systems},
  volume={34},
  pages={17325--17334},
  year={2021}
}

@article{bian,
  title={Continuous dr-submodular maximization: Structure and algorithms},
  author={Bian, An and Levy, Kfir and Krause, Andreas and Buhmann, Joachim M},
  journal={Advances in Neural Information Processing Systems},
  volume={30},
  year={2017}
}

@article{pfohl2022comparison,
  title={A comparison of approaches to improve worst-case predictive model performance over patient subpopulations},
  author={Pfohl, Stephen R and Zhang, Haoran and Xu, Yizhe and Foryciarz, Agata and Ghassemi, Marzyeh and Shah, Nigam H},
  journal={Scientific reports},
  volume={12},
  number={1},
  pages={3254},
  year={2022},
  publisher={Nature Publishing Group UK London}
}

@article{chen2020worst,
  title={Worst-case analysis for randomly collected data},
  author={Chen, Justin and Valiant, Gregory and Valiant, Paul},
  journal={Advances in Neural Information Processing Systems},
  volume={33},
  pages={18183--18193},
  year={2020}
}

@article{so2011deterministic,
  title={Deterministic approximation algorithms for sphere constrained homogeneous polynomial optimization problems},
  author={So, Anthony Man-Cho},
  journal={Mathematical programming},
  volume={129},
  number={2},
  pages={357--382},
  year={2011},
  publisher={Springer}
}

@article{kamyar2014polynomial,
  title={Polynomial optimization with applications to stability analysis and control-alternatives to sum of squares},
  author={Kamyar, Reza and Peet, Matthew},
  journal={arXiv preprint arXiv:1408.5119},
  year={2014}
}

@article{wang2021learning,
  title={Learning mdps from features: Predict-then-optimize for sequential decision making by reinforcement learning},
  author={Wang, Kai and Shah, Sanket and Chen, Haipeng and Perrault, Andrew and Doshi-Velez, Finale and Tambe, Milind},
  journal={Advances in Neural Information Processing Systems},
  volume={34},
  pages={8795--8806},
  year={2021}
}

@inproceedings{elmachtoub2020decision,
  title={Decision trees for decision-making under the predict-then-optimize framework},
  author={Elmachtoub, Adam N and Liang, Jason Cheuk Nam and McNellis, Ryan},
  booktitle={International Conference on Machine Learning},
  pages={2858--2867},
  year={2020},
  organization={PMLR}
}

@inproceedings{mandi2020smart,
  title={Smart predict-and-optimize for hard combinatorial optimization problems},
  author={Mandi, Jayanta and Stuckey, Peter J and Guns, Tias and others},
  booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
  volume={34},
  number={02},
  pages={1603--1610},
  year={2020}
}

@incollection{kuhn2019wasserstein,
  title={Wasserstein distributionally robust optimization: Theory and applications in machine learning},
  author={Kuhn, Daniel and Esfahani, Peyman Mohajerin and Nguyen, Viet Anh and Shafieezadeh-Abadeh, Soroosh},
  booktitle={Operations research \& management science in the age of analytics},
  pages={130--166},
  year={2019},
  publisher={Informs}
}

@book{hart2017pyomo,
  title={Pyomo-optimization modeling in python},
  author={Hart, William E and Laird, Carl D and Watson, Jean-Paul and Woodruff, David L and Hackebeil, Gabriel A and Nicholson, Bethany L and Siirola, John D and others},
  volume={67},
  year={2017},
  publisher={Springer}
}

@article{biegler2009large,
  title={Large-scale nonlinear programming using IPOPT: An integrating framework for enterprise-wide dynamic optimization},
  author={Biegler, Lorenz T and Zavala, Victor M},
  journal={Computers \& Chemical Engineering},
  volume={33},
  number={3},
  pages={575--582},
  year={2009},
  publisher={Elsevier}
}

@article{kaneko1979nash,
  title={The Nash social welfare function},
  author={Kaneko, Mamoru and Nakamura, Kenjiro},
  journal={Econometrica: Journal of the Econometric Society},
  pages={423--435},
  year={1979},
  publisher={JSTOR}
}

@article{vanderschueren2022predict,
  title={Predict-then-optimize or predict-and-optimize? An empirical evaluation of cost-sensitive learning strategies},
  author={Vanderschueren, Toon and Verdonck, Tim and Baesens, Bart and Verbeke, Wouter},
  journal={Information Sciences},
  volume={594},
  pages={400--415},
  year={2022},
  publisher={Elsevier}
}

@inproceedings{robey2022probabilistically,
  title={Probabilistically robust learning: Balancing average and worst-case performance},
  author={Robey, Alexander and Chamon, Luiz and Pappas, George J and Hassani, Hamed},
  booktitle={International Conference on Machine Learning},
  pages={18667--18686},
  year={2022},
  organization={PMLR}
}

@inproceedings{huang2022two,
  title={The two dimensions of worst-case training and their integrated effect for out-of-domain generalization},
  author={Huang, Zeyi and Wang, Haohan and Huang, Dong and Lee, Yong Jae and Xing, Eric P},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  pages={9631--9641},
  year={2022}
}

@incollection{cook2023complexity,
  title={The complexity of theorem-proving procedures},
  author={Cook, Stephen A},
  booktitle={Logic, Automata, and Computational Complexity: The Works of Stephen A. Cook},
  pages={143--152},
  year={2023}
}

@book{karp2010reducibility,
  title={Reducibility among combinatorial problems},
  author={Karp, Richard M},
  year={2010},
  publisher={Springer}
}

@article{levy2020large,
  title={Large-scale methods for distributionally robust optimization},
  author={Levy, Daniel and Carmon, Yair and Duchi, John C and Sidford, Aaron},
  journal={Advances in Neural Information Processing Systems},
  volume={33},
  pages={8847--8860},
  year={2020}
}

@article{rahimian2019distributionally,
  title={Distributionally robust optimization: A review},
  author={Rahimian, Hamed and Mehrotra, Sanjay},
  journal={arXiv preprint arXiv:1908.05659},
  year={2019}
}

@article{thams2022evaluating,
  title={Evaluating robustness to dataset shift via parametric robustness sets},
  author={Thams, Nikolaj and Oberst, Michael and Sontag, David},
  journal={Advances in Neural Information Processing Systems},
  volume={35},
  pages={16877--16889},
  year={2022}
}

@inproceedings{Mokharti,
  title={Conditional gradient method for stochastic submodular maximization: Closing the gap},
  author={Mokhtari, Aryan and Hassani, Hamed and Karbasi, Amin},
  booktitle={International Conference on Artificial Intelligence and Statistics},
  pages={1886--1895},
  year={2018},
  organization={PMLR}
}

@inproceedings{Wilder0,
  title={Preventing infectious disease in dynamic populations under uncertainty},
  author={Wilder, Bryan and Suen, Sze-Chuan and Tambe, Milind},
  booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
  volume={32},
  number={1},
  year={2018}
}

@article{Tang,
  title={PyEPO: A PyTorch-based end-to-end predict-then-optimize library for linear and integer programming},
  author={Tang, Bo and Khalil, Elias B},
  journal={arXiv preprint arXiv:2206.14234},
  year={2022}
}

@article{Duchi,
  title={Learning models with uniform performance via distributionally robust optimization},
  author={Duchi, John C and Namkoong, Hongseok},
  journal={The Annals of Statistics},
  volume={49},
  number={3},
  pages={1378--1406},
  year={2021},
  publisher={Institute of Mathematical Statistics}
}

@inproceedings{Wilder1,
  title={Melding the data-decisions pipeline: Decision-focused learning for combinatorial optimization},
  author={Wilder, Bryan and Dilkina, Bistra and Tambe, Milind},
  booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
  volume={33},
  number={01},
  pages={1658--1665},
  year={2019}
}

@article{Elmachtoub,
  title={Smart “predict, then optimize”},
  author={Elmachtoub, Adam N and Grigas, Paul},
  journal={Management Science},
  volume={68},
  number={1},
  pages={9--26},
  year={2022},
  publisher={INFORMS}
}

@article{Yang,
  title={Change is hard: A closer look at subpopulation shift},
  author={Yang, Yuzhe and Zhang, Haoran and Katabi, Dina and Ghassemi, Marzyeh},
  journal={arXiv preprint arXiv:2302.12254},
  year={2023}
}

@inproceedings{Wilder2,
  title={Distributionally robust submodular maximization},
  author={Staib, Matthew and Wilder, Bryan and Jegelka, Stefanie},
  booktitle={The 22nd International Conference on Artificial Intelligence and Statistics},
  pages={506--516},
  year={2019},
  organization={PMLR}
}

@article{folktables,
  title={Retiring adult: New datasets for fair machine learning},
  author={Ding, Frances and Hardt, Moritz and Miller, John and Schmidt, Ludwig},
  journal={Advances in neural information processing systems},
  volume={34},
  pages={6478--6490},
  year={2021}
}

@inproceedings{hierarchy,
  title={Hierarchical Bayesian models reveal the habitat characteristics of Arctic marine mammals},
  author={M{\"a}kinen, Jussi and Vanhatalo, Jarno},
  booktitle={ECCB2018: 5th European Congress of Conservation Biology. 12th-15th of June 2018, Jyv{\"a}skyl{\"a}, Finland},
  year={2018},
  organization={Open Science Centre, University of Jyv{\"a}skyl{\"a}}
}

@article{Hassani,
  title={Gradient methods for submodular maximization},
  author={Hassani, Hamed and Soltanolkotabi, Mahdi and Karbasi, Amin},
  journal={Advances in Neural Information Processing Systems},
  volume={30},
  year={2017}
}

@article{mulamba2020contrastive,
  title={Contrastive losses and solution caching for predict-and-optimize},
  author={Mulamba, Maxime and Mandi, Jayanta and Diligenti, Michelangelo and Lombardi, Michele and Bucarey, Victor and Guns, Tias},
  journal={arXiv preprint arXiv:2011.05354},
  year={2020}
}

@inproceedings{stuckey2020dynamic,
  title={Dynamic programming for predict+ optimise},
  author={Stuckey, Peter J and Guns, Tias and Bailey, James and Leckie, Christopher and Ramamohanarao, Kotagiri and Chan, Jeffrey and others},
  booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
  volume={34},
  number={02},
  pages={1444--1451},
  year={2020}
}

@inproceedings{LIME,
  title={" Why should i trust you?" Explaining the predictions of any classifier},
  author={Ribeiro, Marco Tulio and Singh, Sameer and Guestrin, Carlos},
  booktitle={Proceedings of the 22nd ACM SIGKDD international conference on knowledge discovery and data mining},
  pages={1135--1144},
  year={2016}
}

@article{Singh,
  title={Generalizability challenges of mortality risk prediction models: A retrospective analysis on a multi-center database},
  author={Singh, Harvineet and Mhasawade, Vishwali and Chunara, Rumi},
  journal={PLOS Digital Health},
  volume={1},
  number={4},
  pages={e0000023},
  year={2022},
  publisher={Public Library of Science San Francisco, CA USA}
}

@article{Roland,
  title={Domain shifts in machine learning based Covid-19 diagnosis from blood tests},
  author={Roland, Theresa and B{\"o}ck, Carl and Tschoellitsch, Thomas and Maletzky, Alexander and Hochreiter, Sepp and Meier, Jens and Klambauer, G{\"u}nter},
  journal={Journal of Medical Systems},
  volume={46},
  number={5},
  pages={23},
  year={2022},
  publisher={Springer}
}

@article{Liu,
  title={On the Need for a Language Describing Distribution Shifts: Illustrations on Tabular Datasets},
  author={Liu, Jiashuo and Wang, Tianyu and Cui, Peng and Namkoong, Hongseok},
  journal={arXiv preprint arXiv:2307.05284},
  year={2023}
}

@article{Trehan,
  title={Predictive Algorithms in the Public Sector},
  author={Trehan, Vishal}
}

@article{mo2021learning,
  title={Learning optimal distributionally robust individualized treatment rules},
  author={Mo, Weibin and Qi, Zhengling and Liu, Yufeng},
  journal={Journal of the American Statistical Association},
  volume={116},
  number={534},
  pages={659--674},
  year={2021},
  publisher={Taylor \& Francis}
}

@article{luedtke2016optimal,
  title={Optimal individualized treatments in resource-limited settings},
  author={Luedtke, Alexander R and van der Laan, Mark J},
  journal={The international journal of biostatistics},
  volume={12},
  number={1},
  pages={283--303},
  year={2016},
  publisher={De Gruyter}
}

@inproceedings{verma2023increasing,
  title={Increasing impact of mobile health programs: SAHELI for maternal and child care},
  author={Verma, Shresth and Singh, Gargi and Mate, Aditya and Verma, Paritosh and Gorantla, Sruthi and Madhiwalla, Neha and Hegde, Aparna and Thakkar, Divy and Jain, Manish and Tambe, Milind and others},
  booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
  volume={37},
  number={13},
  pages={15594--15602},
  year={2023}
}

@article{athey2023machine,
  title={Machine learning who to nudge: causal vs predictive targeting in a field experiment on student financial aid renewal},
  author={Athey, Susan and Keleher, Niall and Spiess, Jann},
  journal={arXiv preprint arXiv:2310.08672},
  year={2023}
}

@article{wang2022against,
  title={Against predictive optimization: On the legitimacy of decision-making algorithms that optimize predictive accuracy},
  author={Wang, Angelina and Kapoor, Sayash and Barocas, Solon and Narayanan, Arvind},
  journal={Available at SSRN},
  year={2022}
}

@article{schultz2019risk,
  title={Risk assessment models for potential use in the emergency department have lower predictive ability in older patients compared to the middle-aged for short-term mortality--a retrospective cohort study},
  author={Schultz, Martin and Rasmussen, Line Jee Hartmann and Carlson, Nicolas and Hasselbalch, Rasmus Bo and Jensen, Birgitte Nybo and Usinger, Lotte and Eugen-Olsen, Jesper and Torp-Pedersen, Christian and Rasmussen, Lars Simon and Iversen, Kasper Karmark},
  journal={BMC geriatrics},
  volume={19},
  pages={1--9},
  year={2019},
  publisher={Springer}
}

@article{orbanz2014bayesian,
  title={Bayesian models of graphs, arrays and other exchangeable random structures},
  author={Orbanz, Peter and Roy, Daniel M},
  journal={IEEE transactions on pattern analysis and machine intelligence},
  volume={37},
  number={2},
  pages={437--461},
  year={2014},
  publisher={IEEE}
}

@article{raita2019emergency,
  title={Emergency department triage prediction of clinical outcomes using machine learning models},
  author={Raita, Yoshihiko and Goto, Tadahiro and Faridi, Mohammad Kamal and Brown, David FM and Camargo, Carlos A and Hasegawa, Kohei},
  journal={Critical care},
  volume={23},
  number={1},
  pages={1--13},
  year={2019},
  publisher={BioMed Central}
}

@inproceedings{johnson2023characterizing,
  title={Characterizing and Improving the Robustness of Predict-Then-Optimize Frameworks},
  author={Johnson-Yu, Sonja and Finocchiaro, Jessie and Wang, Kai and Vorobeychik, Yevgeniy and Sinha, Arunesh and Taneja, Aparna and Tambe, Milind},
  booktitle={International Conference on Decision and Game Theory for Security},
  pages={133--152},
  year={2023},
  organization={Springer}
}

@article{namkoong2016stochastic,
  title={Stochastic gradient methods for distributionally robust optimization with f-divergences},
  author={Namkoong, Hongseok and Duchi, John C},
  journal={Advances in neural information processing systems},
  volume={29},
  year={2016}
}

@article{rockafellar2023distributional,
  title={DISTRIBUTIONAL ROBUSTNESS, STOCHASTIC DIVERGENCES, AND THE QUADRANGLE OF RISK},
  author={Rockafellar, R Tyrrell},
  year={2023}
}

@article{li2020does,
  title={How does momentum help Frank Wolfe?},
  author={Li, Bingcong and Coutino, Mario and Giannakis, Georgios B and Leus, Geert},
  journal={arXiv preprint arXiv:2006.11116},
  year={2020}
}

@TechReport{mitchell80,
  author = 	 "T. M. Mitchell",
  title = 	 "The Need for Biases in Learning Generalizations",
  institution =  "Computer Science Department, Rutgers University",
  year = 	 "1980",
  address =	 "New Brunswick, MA",
}

@phdthesis{kearns89,
  author = {M. J. Kearns},
  title =  {Computational Complexity of Machine Learning},
  school = {Department of Computer Science, Harvard University},
  year =   {1989}
}

@article{haendel2021national,
  title={The National COVID Cohort Collaborative (N3C): rationale, design, infrastructure, and deployment},
  author={Haendel, Melissa A and Chute, Christopher G and Bennett, Tellen D and Eichmann, David A and Guinney, Justin and Kibbe, Warren A and Payne, Philip RO and Pfaff, Emily R and Robinson, Peter N and Saltz, Joel H and others},
  journal={Journal of the American Medical Informatics Association},
  volume={28},
  number={3},
  pages={427--443},
  year={2021},
  publisher={Oxford University Press}
}

@Book{MachineLearningI,
  editor = 	 "R. S. Michalski and J. G. Carbonell and T.
		  M. Mitchell",
  title = 	 "Machine Learning: An Artificial Intelligence
		  Approach, Vol. I",
  publisher = 	 "Tioga",
  year = 	 "1983",
  address =	 "Palo Alto, CA"
}

@Book{DudaHart2nd,
  author =       "R. O. Duda and P. E. Hart and D. G. Stork",
  title =        "Pattern Classification",
  publisher =    "John Wiley and Sons",
  edition =      "2nd",
  year =         "2000"
}

@misc{anonymous,
  title= {Suppressed for Anonymity},
  author= {Author, N. N.},
  year= {2021}
}

@InCollection{Newell81,
  author =       "A. Newell and P. S. Rosenbloom",
  title =        "Mechanisms of Skill Acquisition and the Law of
                  Practice", 
  booktitle =    "Cognitive Skills and Their Acquisition",
  pages =        "1--51",
  publisher =    "Lawrence Erlbaum Associates, Inc.",
  year =         "1981",
  editor =       "J. R. Anderson",
  chapter =      "1",
  address =      "Hillsdale, NJ"
}


@Article{Samuel59,
  author = 	 "A. L. Samuel",
  title = 	 "Some Studies in Machine Learning Using the Game of
		  Checkers",
  journal =	 "IBM Journal of Research and Development",
  year =	 "1959",
  volume =	 "3",
  number =	 "3",
  pages =	 "211--229"
}
