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@inproceedings{Bareinboim2014:selectionbias,
title = {Recovering from Selection Bias in Causal and Statistical Inference},
author = {Bareinboim, E. and Tian, J. and Pearl, J.},
booktitle = {Proceedings of the 28th AAAI Conference on Neural Information Processing Systems},
year = {2014}
}
@inproceedings{Shpitser2015,
title = {Missing Data as a Causal and Probabilistic Problem},
author = {Shpitser, I. and Mohan, K. and Pearl, J.},
editor = {Marina Meila and Tom Heskes},
booktitle = {Proceedings of the 31st Conference on Uncertainty in Artificial Intelligence},
publisher = {AUAI Press},
pages = {802--811},
year = {2015}
}
@inproceedings{Mohan2013,
author = {K. Mohan and J. Pearl and J. Tian},
title = {Graphical models for inference with missing data},
booktitle = {Advances in Neural Information Systems},
volume = {26},
pages = {1277--1285},
year = {2013}
}
@incollection{smr1999,
author={Peter Spirtes and Christopher Meek and Thomas Richardson},
title={An Algorithm for Causal Inference in the Presence of Latent Variables and Selection Bias},
booktitle={Computation, Causation \& Discovery},
editor = {Clark Glymour and Gregory F. Cooper},
year = {1999},
pages = {211--252},
publisher = { AAAI / MIT Press}
}
@article{holland1986statistics,
title={Statistics and causal inference},
author={Holland, Paul W},
journal={Journal of the American statistical Association},
volume={81},
number={396},
pages={945--960},
year={1986},
publisher={Taylor \& Francis}
}
@inproceedings{kallus2018confounding,
title={Confounding-robust policy improvement},
author={Kallus, Nathan and Zhou, Angela},
booktitle={Advances in neural information processing systems},
pages={9269--9279},
year={2018}
}
@inproceedings{DBLP:conf/icml/ThomasB16,
author = {Philip S. Thomas and
Emma Brunskill},
editor = {Maria{-}Florina Balcan and
Kilian Q. Weinberger},
title = {Data-Efficient Off-Policy Policy Evaluation for Reinforcement Learning},
booktitle = {Proceedings of the 33nd International Conference on Machine Learning,
{ICML} 2016, New York City, NY, USA, June 19-24, 2016},
series = {{JMLR} Workshop and Conference Proceedings},
volume = {48},
pages = {2139--2148},
publisher = {JMLR.org},
year = {2016},
OPTurl = {http://proceedings.mlr.press/v48/thomasa16.html},
OPTtimestamp = {Wed, 29 May 2019 08:41:46 +0200},
OPTbiburl = {https://dblp.org/rec/bib/conf/icml/ThomasB16},
OPTbibsource = {dblp computer science bibliography, https://dblp.org}
}
@article{chouldechova2017fair,
title={Fair prediction with disparate impact: A study of bias in recidivism prediction instruments},
author={Chouldechova, Alexandra},
journal={Big data},
volume={5},
number={2},
pages={153--163},
year={2017},
publisher={Mary Ann Liebert, Inc. 140 Huguenot Street, 3rd Floor New Rochelle, NY 10801 USA}
}
@article{mccandless2017comparison,
title={A comparison of Bayesian and Monte Carlo sensitivity analysis for unmeasured confounding},
author={McCandless, Lawrence C and Gustafson, Paul},
journal={Statistics in medicine},
volume={36},
number={18},
pages={2887--2901},
year={2017},
publisher={Wiley Online Library}
}
@article{kleinberg2018human,
title={Human decisions and machine predictions},
author={Kleinberg, Jon and Lakkaraju, Himabindu and Leskovec, Jure and Ludwig, Jens and Mullainathan, Sendhil},
journal={The quarterly journal of economics},
volume={133},
number={1},
pages={237--293},
year={2018},
publisher={Oxford University Press}
}
@inproceedings{corbett2017algorithmic,
title={Algorithmic decision making and the cost of fairness},
author={Corbett-Davies, Sam and Pierson, Emma and Feller, Avi and Goel, Sharad and Huq, Aziz},
booktitle={Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining},
pages={797--806},
year={2017}
}
@inproceedings{coston2020counterfactual,
title={Counterfactual risk assessments, evaluation, and fairness},
author={Coston, Amanda and Mishler, Alan and Kennedy, Edward H and Chouldechova, Alexandra},
booktitle={Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency},
pages={582--593},
year={2020}
}
@inproceedings{madras2019fairness,
title={Fairness through causal awareness: Learning causal latent-variable models for biased data},
author={Madras, David and Creager, Elliot and Pitassi, Toniann and Zemel, Richard},
booktitle={Proceedings of the Conference on Fairness, Accountability, and Transparency},
pages={349--358},
year={2019}
}
@article{murder,
OPTISSN = {09641998, 1467985X},
OPTURL = {http://www.jstor.org/stable/30136747},
author = {Richard Berk and Lawrence Sherman and Geoffrey Barnes and Ellen Kurtz and Lindsay Ahlman},
journal = {Journal of the Royal Statistical Society. Series A (Statistics in Society)},
number = {1},
pages = {191--211},
publisher = {[Wiley, Royal Statistical Society]},
title = {Forecasting Murder within a Population of Probationers and Parolees: A High Stakes Application of Statistical Learning},
volume = {172},
year = {2009}
}
@book{little2019statistical,
title={Statistical analysis with missing data},
author={Little, Roderick JA and Rubin, Donald B},
volume={793},
year={2019},
publisher={John Wiley \& Sons}
}
@article{bang2005doubly,
title={Doubly robust estimation in missing data and causal inference models},
author={Bang, Heejung and Robins, James M},
journal={Biometrics},
volume={61},
number={4},
pages={962--973},
year={2005},
publisher={Wiley Online Library}
}
@inproceedings{DBLP:conf/icml/DudikLL11,
author = {Miroslav Dud{\'{\i}}k and
John Langford and
Lihong Li},
editor = {Lise Getoor and
Tobias Scheffer},
title = {Doubly Robust Policy Evaluation and Learning},
booktitle = {Proceedings of the 28th International Conference on Machine Learning,
{ICML} 2011, Bellevue, Washington, USA, June 28 - July 2, 2011},
pages = {1097--1104},
publisher = {Omnipress},
year = {2011},
OPTurl = {https://icml.cc/2011/papers/554\_icmlpaper.pdf},
OPTtimestamp = {Wed, 03 Apr 2019 17:43:35 +0200},
OPTbiburl = {https://dblp.org/rec/bib/conf/icml/DudikLL11},
OPTbibsource = {dblp computer science bibliography, https://dblp.org}
}
@inproceedings{Jung2,
author = {Jung, Jongbin and Shroff, Ravi and Feller, Avi and Goel, Sharad},
title = {Bayesian Sensitivity Analysis for Offline Policy Evaluation},
year = {2020},
isbn = {9781450371100},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
OPTurl = {https://doi.org/10.1145/3375627.3375822},
OPTdoi = {10.1145/3375627.3375822},
booktitle = {Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society},
pages = {64?70},
numpages = {7},
OPTkeywords = {pretrial risk assessment, offline policy evaluation, sensitivity to unmeasured confounding},
OPTlocation = {New York, NY, USA},
OPTseries = {AIES}
}
@inproceedings{DBLP:conf/icml/JohanssonSS16,
author = {Fredrik D. Johansson and
Uri Shalit and
David A. Sontag},
editor = {Maria{-}Florina Balcan and
Kilian Q. Weinberger},
title = {Learning Representations for Counterfactual Inference},
booktitle = {Proceedings of the 33nd International Conference on Machine Learning,
{ICML} 2016, New York City, NY, USA, June 19-24, 2016},
series = {{JMLR} Workshop and Conference Proceedings},
volume = {48},
pages = {3020--3029},
publisher = {JMLR.org},
year = {2016},
url = {http://proceedings.mlr.press/v48/johansson16.html},
timestamp = {Fri, 15 Nov 2019 17:16:09 +0100},
biburl = {https://dblp.org/rec/bib/conf/icml/JohanssonSS16},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
@article{DBLP:journals/jmlr/BottouPCCCPRSS13,
author = {L{\'{e}}on Bottou and
Jonas Peters and
Joaquin Qui{\~{n}}onero Candela and
Denis Xavier Charles and
Max Chickering and
Elon Portugaly and
Dipankar Ray and
Patrice Y. Simard and
Ed Snelson},
title = {Counterfactual reasoning and learning systems: the example of computational
advertising},
journal = {J. Mach. Learn. Res.},
volume = {14},
number = {1},
pages = {3207--3260},
year = {2013},
url = {http://dl.acm.org/citation.cfm?id=2567766},
timestamp = {Wed, 10 Jul 2019 15:27:56 +0200},
biburl = {https://dblp.org/rec/bib/journals/jmlr/BottouPCCCPRSS13},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
@inproceedings{DBLP:conf/icml/NabiMS19,
author = {Razieh Nabi and
Daniel Malinsky and
Ilya Shpitser},
OPTaddress = { {ICML} 2019, 9-15 June 2019, Long Beach, California, {USA}},
OPTeditor = {Kamalika Chaudhuri and
Ruslan Salakhutdinov},
title = {Learning Optimal Fair Policies},
booktitle = {Proceedings of the 36th International Conference on Machine Learning},
series = {Proceedings of Machine Learning Research},
volume = {97},
pages = {4674--4682},
publisher = {{PMLR}},
year = {2019},
OPTurl = {http://proceedings.mlr.press/v97/nabi19a.html},
OPTtimestamp = {Tue, 11 Jun 2019 15:37:38 +0200},
OPTbiburl = {https://dblp.org/rec/bib/conf/icml/NabiMS19},
OPTbibsource = {dblp computer science bibliography, https://dblp.org}
}
@article{rosenbaum1983central,
title={The central role of the propensity score in observational studies for causal effects},
author={Rosenbaum, Paul R and Rubin, Donald B},
journal={Biometrika},
volume={70},
number={1},
pages={41--55},
year={1983},
publisher={Oxford University Press}
}
@article{austin2011introduction,
title={An introduction to propensity score methods for reducing the effects of confounding in observational studies},
author={Austin, Peter C},
journal={Multivariate behavioral research},
volume={46},
number={3},
pages={399--424},
year={2011},
publisher={Taylor \& Francis}
}
@book{pearl2000,
author = {J.~Pearl},
title = {Causality: Models, Reasoning, and Inference},
publisher = {Cambridge University Press},
year = {2000}
}
@article{pearl1995empirical,
title={Causal diagrams for empirical research},
author={Pearl, Judea},
journal={Biometrika},
volume={82},
number={4},
pages={669--688},
year={1995},
publisher={Oxford University Press}
}
@article{brennan2009evaluating,
title={Evaluating the predictive validity of the COMPAS risk and needs assessment system},
author={Brennan, Tim and Dieterich, William and Ehret, Beate},
journal={Criminal Justice and Behavior},
volume={36},
number={1},
pages={21--40},
year={2009},
publisher={Sage Publications Sage CA: Los Angeles, CA}
}
@article{hernan2004structural,
title={A structural approach to selection bias},
author={Hern{\'a}n, Miguel A and Hern{\'a}ndez-D{\'\i}az, Sonia and Robins, James M},
journal={Epidemiology},
volume={15},
number={5},
pages={615--625},
year={2004},
publisher={LWW}
}
@inproceedings{DBLP:conf/icml/Kusner0LS19,
author = {Matt J. Kusner and
Chris Russell and
Joshua R. Loftus and
Ricardo Silva},
title = {Making Decisions that Reduce Discriminatory Impacts},
booktitle = {{ICML}},
series = {Proceedings of Machine Learning Research},
volume = {97},
pages = {3591--3600},
publisher = {{PMLR}},
year = {2019}
}
@inproceedings{tolan2019why,
OPTAcmid = {3326705},
OPTAddress = {New York, NY, USA},
Author = {Tolan, Song\"{u}l and Miron, Marius and G\'{o}mez, Emilia and Castillo, Carlos},
Booktitle = {Proceedings of the Seventeenth International Conference on Artificial Intelligence and Law},
OPTDate-Added = {2019-08-02 06:37:23 +0000},
OPTDate-Modified = {2019-08-02 06:38:23 +0000},
OPTDoi = {10.1145/3322640.3326705},
OPTIsbn = {978-1-4503-6754-7},
OPTKeywords = {algorithmic bias, algorithmic fairness, criminal recidivism, machine learning, risk assessment},
OPTLocation = {Montreal, QC, Canada},
OPTNumpages = {10},
Pages = {83--92},
Publisher = {ACM},
OPTSeries = {ICAIL '19},
Title = {Why Machine Learning May Lead to Unfairness: Evidence from Risk Assessment for Juvenile Justice in Catalonia},
OPTUrl = {http://doi.acm.org/10.1145/3322640.3326705},
Year = {2019}
}
@article{pearl2010introduction,
Author = {Pearl, Judea},
Journal = {The international journal of biostatistics},
Number = {2},
Publisher = {De Gruyter},
Title = {An introduction to causal inference},
Volume = {6},
Year = {2010}}
@book{bookofwhy,
title={The book of why: the new science of cause and effect},
author={Pearl, Judea and Mackenzie, Dana},
year={2018},
publisher={Basic Books},
address = {New York, USA}
}
@inproceedings{lakkaraju2017selective,
OPTAcmid = {3098066},
OPTAddress = {New York, NY, USA},
Author = {Lakkaraju, Himabindu and Kleinberg, Jon and Leskovec, Jure and Ludwig, Jens and Mullainathan, Sendhil},
Booktitle = {Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining},
OPTDoi = {10.1145/3097983.3098066},
OPTIsbn = {978-1-4503-4887-4},
OPTKeywords = {evaluating machine learning algorithms, selective labels, unmeasured confounders, unobservables},
OPTLocation = {Halifax, NS, Canada},
Numpages = {10},
Pages = {275--284},
Publisher = {ACM},
Series = {KDD '17},
Title = {The Selective Labels Problem: Evaluating Algorithmic Predictions in the Presence of Unobservables},
OPTUrl = {http://doi.acm.org/10.1145/3097983.3098066},
Year = {2017},
OPTBdsk-Url-1 = {http://doi.acm.org/10.1145/3097983.3098066},
OPTBdsk-Url-2 = {http://dx.doi.org/10.1145/3097983.3098066}}
@article{jung2018algorithmic,
Author = {Jung, Jongbin and Shroff, Ravi and Feller, Avi and Goel, Sharad},
Date-Added = {2019-08-02 06:37:23 +0000},
Date-Modified = {2019-08-02 06:37:23 +0000},
Journal = {arXiv preprint arXiv:1805.01868},
Title = {Algorithmic decision making in the presence of unmeasured confounding},
Year = {2018}}
@article{dearteaga2018learning,
Author = {De-Arteaga, Maria and Dubrawski, Artur and Chouldechova, Alexandra},
Date-Added = {2019-08-02 06:37:23 +0000},
Date-Modified = {2019-08-02 06:37:23 +0000},
Journal = {arXiv preprint arXiv:1807.00905},
Title = {Learning under selective labels in the presence of expert consistency},
Year = {2018}}
@article{ohagan1979outlier,
title={On outlier rejection phenomena in Bayes inference},
author={O'Hagan, Anthony},
journal={Journal of the Royal Statistical Society: Series B (Methodological)},
volume={41},
number={3},
pages={358--367},
year={1979},
publisher={Wiley Online Library}
}
@inproceedings{bareinboim2012controlling,
title={Controlling selection bias in causal inference},
author={Bareinboim, Elias and Pearl, Judea},
booktitle={Artificial Intelligence and Statistics},
pages={100--108},
year={2012}
}
@misc{kleinberg2016inherent,
title={Inherent Trade-Offs in the Fair Determination of Risk Scores},
author={Jon Kleinberg and Sendhil Mullainathan and Manish Raghavan},
year={2016},
eprint={1609.05807},
archivePrefix={arXiv},
primaryClass={cs.LG}
}
@article{angwin2016machine,
title={Machine Bias},
url={https://www.propublica.org/article/machine-bias-risk-assessments-in-criminal-sentencing},
journal={ProPublica},
year = {2016},
author={Julia Angwin and Jeff Larson and Surya Mattu and Lauren Kirchner}
}
@article{mccandless2007bayesian,
title={Bayesian sensitivity analysis for unmeasured confounding in observational studies},
author={McCandless, Lawrence C and Gustafson, Paul and Levy, Adrian},
journal={Statistics in medicine},
volume={26},
number={11},
pages={2331--2347},
year={2007},
publisher={Wiley Online Library}
}