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In an attempt to make algorithms fair, the machine learning literature has largely focused on equalizing decisions, outcomes, or error rates across race or gender groups.
Fair Division: From cake-cutting to dispute resolution
Steven J Brams, Steven John Brams, and Alan D Taylor · 1996
Earlier work this paper cites.
Determinant maximization with linear matrix inequality constraints
Lieven Vandenberghe, Stephen Boyd, and Shao-Po Wu · 1998
Earlier work this paper cites.
Pretrial services programs: Responsibilities and potential
Barry Mahoney, Bruce D Beaudin, John A Carver III, Daniel B Ryan, and Richard B Hoffman · 2001
Earlier work this paper cites.
Finite-time analysis of the multiarmed bandit problem
Peter Auer, Nicolo Cesa-Bianchi, and Paul Fischer · 2002
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The sample complexity of exploration in the multi-armed bandit problem
Shie Mannor and John N. Tsitsiklis · 2004
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Preference learning with Gaussian processes
Wei Chu and Zoubin Ghahramani · 2005
Earlier work this paper cites.
A Unifying Framework for. Computational Reinforcement Learning Theory
L. Li · 2009
Earlier work this paper cites.
Preference learning and ranking by pairwise comparison
Johannes Fürnkranz and Eyke Hüllermeier · 2010
Earlier work this paper cites.
The creation and validation of the ohio risk assessment system (oras)
Edward J Latessa, Richard Lemke, Matthew Makarios, and Paula Smith · 2010
Earlier work this paper cites.
Improved algorithms for linear stochastic bandits
Yasin Abbasi-Yadkori, Dávid Pál, and Csaba Szepesvári · 2011
Earlier work this paper cites.
The price of fairness
Dimitris Bertsimas, Vivek F. Farias, and Nikolaos Trichakis · 2011
Earlier work this paper cites.
Implementing risk assessment in the federal pretrial services system
Timothy P Cadigan and Christopher T Lowenkamp · 2011
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An empirical evaluation of thompson sampling
Olivier Chapelle and Lihong Li · 2011
Earlier work this paper cites.
Optimal envy-free cake cutting
Yuga J Cohler, John K Lai, David C Parkes, and Ariel D Procaccia · 2011
Earlier work this paper cites.
The efficiency of fair division
Ioannis Caragiannis, Christos Kaklamanis, Panagiotis Kanellopoulos, and Maria Kyropoulou · 2012
Earlier work this paper cites.
The kidney allocation system
John J Friedewald, Ciara J Samana, Bertram L Kasiske, Ajay K Israni, Darren Stewart, Wida Cherikh, and Richard N Formica · 2013
Earlier work this paper cites.
Cake cutting: Not just child’s play
Ariel D Procaccia · 2013
Earlier work this paper cites.
Active learning for multi-objective optimization
Marcela Zuluaga, Guillaume Sergent, Andreas Krause, and Markus Püschel · 2013
Earlier work this paper cites.
Resourceful contextual bandits
Ashwinkumar Badanidiyuru, John Langford, and Aleksandrs Slivkins · 2014
Earlier work this paper cites.
Random design analysis of ridge regression, 2014
Daniel Hsu, Sham M. Kakade, and Tong Zhang · 2014
Earlier work this paper cites.
Pretrial risk assessment: Improving public safety and fairness in pretrial decision making
Anne Milgram, Alexander M Holsinger, Marie Vannostrand, and Matthew W Alsdorf · 2014
Earlier work this paper cites.
Certifying and removing disparate impact
Michael Feldman, Sorelle A Friedler, John Moeller, Carlos Scheidegger, and Suresh Venkatasubramanian · 2015
Earlier work this paper cites.
Algorithms with logarithmic or sublinear regret for constrained contextual bandits
Huasen Wu, R Srikant, Xin Liu, and Chong Jiang · 2015
Earlier work this paper cites.
A near-optimal exploration-exploitation approach for assortment selection
Shipra Agrawal, Vashist Avadhanula, Vineet Goyal, and Assaf Zeevi · 2016
Earlier work this paper cites.
Equality of opportunity in supervised learning
Moritz Hardt, Eric Price, and Nati Srebro · 2016
Earlier work this paper cites.
Racial disparity in natural language processing: A case study of social media African-American English
Su Lin Blodgett and Brendan O’Connor · 2017
Earlier work this paper cites.
Semantics derived automatically from language corpora contain human-like biases
Aylin Caliskan, Joanna J. Bryson, and Arvind Narayanan · 2017
Earlier work this paper cites.
Algorithmic decision making and the cost of fairness
Sam Corbett-Davies, Emma Pierson, Avi Feller, Sharad Goel, and Aziz Huq · 2017
Earlier work this paper cites.
Which is the fairest (rent division) of them all?
Ya’akov Gal, Moshe Mash, Ariel D Procaccia, and Yair Zick · 2017
Earlier work this paper cites.
Avoiding discrimination through causal reasoning
Niki Kilbertus, Mateo Rojas Carulla, Giambattista Parascandolo, Moritz Hardt, Dominik Janzing, and Bernhard Schölkopf · 2017
Earlier work this paper cites.
Counterfactual fairness
Matt J Kusner, Joshua Loftus, Chris Russell, and Ricardo Silva · 2017
Earlier work this paper cites.
Provably optimal algorithms for generalized linear contextual bandits
Lihong Li, Yu Lu, and Dengyong Zhou · 2017
Earlier work this paper cites.
Predictive analytics for city agencies: Lessons from children’s services
Ravi Shroff · 2017
Earlier work this paper cites.
Interventions over predictions: Reframing the ethical debate for actuarial risk assessment
Chelsea Barabas, Madars Virza, Karthik Dinakar, Joichi Ito, and Jonathan Zittrain · 2018
Cited alongside, same era.
Gender shades: Intersectional accuracy disparities in commercial gender classification
Joy Buolamwini and Timnit Gebru · 2018
Cited alongside, same era.
Rideshare-based medical transportation for medicaid patients and primary care show rates: a difference-in-difference analysis of a pilot program
Krisda H Chaiyachati, Rebecca A Hubbard, Alyssa Yeager, Brian Mugo, Judy A Shea, Roy Rosin, and David Grande · 2018
Cited alongside, same era.
A causal bayesian networks viewpoint on fairness
Silvia Chiappa and William S Isaac · 2018
Cited alongside, same era.
A case study of algorithm-assisted decision making in child maltreatment hotline screening decisions
Alexandra Chouldechova, Diana Benavides-Prado, Oleksandr Fialko, and Rhema Vaithianathan · 2018
Cited alongside, same era.
Fairness and utilization in allocating resources with uncertain demand
Kate Donahue and Jon Kleinberg · 2020
Later among the works it cites.
Behavioral nudges reduce failure to appear for court
Alissa Fishbane, Aurelie Ouss, and Anuj K Shah · 2020
Later among the works it cites.
arm: Data Analysis Using Regression and Multilevel/Hierarchical Models , 2020
Andrew Gelman and Yu-Sung Su · 2020
Later among the works it cites.
Too many fairness metrics: Is there a solution?
Swati Gupta, Akhil Jalan, Gireeja Ranade, Helen Yang, and Simon Zhuang · 2020
Later among the works it cites.
Racial disparities in automated speech recognition
Allison Koenecke, Andrew Nam, Emily Lake, Joe Nudell, Minnie Quartey, Zion Mengesha, Connor Toups, John R Rickford, Dan Jurafsky, and Sharad Goel · 2020
Later among the works it cites.
Bandit algorithms
Tor Lattimore and Csaba Szepesvári · 2020
Later among the works it cites.
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Discrimination in online advertising: A multidisciplinary inquiry
Amit Datta, Anupam Datta, Jael Makagon, Deirdre K Mulligan, and Michael Carl Tschantz · 2018
Cited alongside, same era.
The accuracy, equity, and jurisprudence of criminal risk assessment
Sharad Goel, Ravi Shroff, Jennifer L Skeem, and Christopher Slobogin · 2018
Cited alongside, same era.
Machine learning, health disparities, and causal reasoning
Steven N Goodman, Sharad Goel, and Mark R Cullen · 2018
Cited alongside, same era.
Is q-learning provably efficient?
Chi Jin, Zeyuan Allen-Zhu, Sebastien Bubeck, and Michael I Jordan · 2018
Cited alongside, same era.
Delayed impact of fair machine learning
Lydia T Liu, Sarah Dean, Esther Rolf, Max Simchowitz, and Moritz Hardt · 2018
Cited alongside, same era.
Fair inference on outcomes
Razieh Nabi and Ilya Shpitser · 2018
Cited alongside, same era.
Fairness in decision-making — the causal explanation formula
Junzhe Zhang and Elias Bareinboim · 2018
Cited alongside, same era.
Preference learning for real-world multi-objective decision making
Zhiyuan (Jerry) Lin, Adam Obeng, and Eytan Bakshy · 2020
Later among the works it cites.
Modernizing medical transportation with rideshare
Lyft · 2020
Later among the works it cites.
Finite-sample analysis of m-estimators using self-concordance, 2020
Dmitrii Ostrovskii and Francis Bach · 2020
Later among the works it cites.
Balancing competing objectives with noisy data: Score-based classifiers for welfare-aware machine learning
Esther Rolf, Max Simchowitz, Sarah Dean, Lydia T Liu, Daniel Bjorkegren, Moritz Hardt, and Joshua Blumenstock · 2020
Later among the works it cites.
Rides for refugees: A transportation assistance pilot for women’s health
Simone Vais, Justin Siu, Sheela Maru, Jodi Abbott, Ingrid St Hill, Confidence Achilike, Wan-Ju Wu, Tejumola M Adegoke, and Courtney Steer-Massaro · 2020
Later among the works it cites.
Going to the doctor: Rideshare as nonemergency medical transportation
Laura Fraade-Blanar, Tina Koo, and Christopher M. Whaley · 2021
Closest in time.
Confidence intervals for policy evaluation in adaptive experiments
Vitor Hadad, David A Hirshberg, Ruohan Zhan, Stefan Wager, and Susan Athey · 2021
Closest in time.
Improved confidence bounds for the linear logistic model and applications to bandits
Kwang-Sung Jun, Lalit Jain, Blake Mason, and Houssam Nassif · 2021
Closest in time.
Fairness, equality, and power in algorithmic decision-making
Maximilian Kasy and Rediet Abebe · 2021
Closest in time.
Breaking taboos in fair machine learning: An experimental study
Julian Nyarko, Sharad Goel, and Roseanna Sommers · 2021
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Achieving fairness in the stochastic multi-armed bandit problem
Vishakha Patil, Ganesh Ghalme, Vineet Nair, and Y Narahari · 2021
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Clinical trial of an AI-augmented intervention for HIV prevention in youth experiencing homelessness
Bryan Wilder, Laura Onasch-Vera, Graham Diguiseppi, Robin Petering, Chyna Hill, Amulya Yadav, Eric Rice, and Milind Tambe · 2021
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Design of experiments for stochastic contextual linear bandits
Andrea Zanette, Kefan Dong, Jonathan N Lee, and Emma Brunskill · 2021
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Statistical inference with m-estimators on adaptively collected data
Kelly Zhang, Lucas Janson, and Susan Murphy · 2021
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Can transportation subsidies reduce failures to appear in criminal court? evidence from a pilot randomized controlled trial
Rebecca Brough, Matthew Freedman, Daniel E. Ho, and David C. Phillips · 2022
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Fairness-oriented learning for optimal individualized treatment rules
Ethan X Fang, Zhaoran Wang, and Lan Wang · 2022
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Dimensions of diversity in human perceptions of algorithmic fairness
Nina Grgić-Hlača, Gabriel Lima, Adrian Weller, and Elissa M. Redmiles · 2022
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Instance-optimal pac algorithms for contextual bandits
Zhaoqi Li, Lillian Ratliff, Kevin G Jamieson, Lalit Jain, et al · 2022
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Causal conceptions of fairness and their consequences
Hamed Nilforoshan, Johann D Gaebler, Ravi Shroff, and Sharad Goel · 2022
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Illegible courts and failure to appear
Sophie Allen · 2023
Closest in time.
Fairness and Machine Learning: Limitations and Opportunities
Solon Barocas, Moritz Hardt, and Arvind Narayanan · 2023
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The measure and mismeasure of fairness
Sam Corbett-Davies, Johann Gaebler, Hamed Nilforoshan, Ravi Shroff, and Sharad Goel · 2023
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Popular support for balancing equity and efficiency in resource allocation: A case study in online advertising to increase welfare program awareness
Allison Koenecke, Eric Giannella, Robb Willer, and Sharad Goel · 2023
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Experiment planning with function approximation
Aldo Pacchiano, Jonathan Lee, and Emma Brunskill · 2023
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Fair policy targeting
Davide Viviano and Jelena Bradic · 2023
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Court date reminders reduce court nonappearance: A meta-analysis
Samantha A. Zottola, William E. Crozier, Deniz Ariturk, and Sarah L. Desmarais · 2023
Closest in time.