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While machine learning can myopically reinforce social inequalities, it may also be used to dynamically seek equitable outcomes.
Will affirmative-action policies eliminate negative stereotypes?
Stephen Coate and Glenn C Loury · 1993
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Finite-time analysis of the multiarmed bandit problem
Peter Auer, Nicolo Cesa-Bianchi, and Paul Fischer · 2002
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Fairness through awareness
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Learning fair representations
Rich Zemel, Yu Wu, Kevin Swersky, Toni Pitassi, and Cynthia Dwork · 2013
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Certifying and removing disparate impact
Michael Feldman, Sorelle A Friedler, John Moeller, Carlos Scheidegger, and Suresh Venkatasubramanian · 2015
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There is a blind spot in AI research
Kate Crawford and Ryan Calo · 2016
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Equality of opportunity in supervised learning, 2016
Moritz Hardt, Eric Price, and Nathan Srebro · 2016
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Fairness in learning: Classic and contextual bandits
Matthew Joseph, Michael Kearns, Jamie H Morgenstern, and Aaron Roth · 2016
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UCI machine learning repository, 2017
Dheeru Dua and Casey Graff · 2017
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Fairness in reinforcement learning
Shahin Jabbari, Matthew Joseph, Michael Kearns, Jamie Morgenstern, and Aaron Roth · 2017
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Calibrated fairness in bandits
Yang Liu, Goran Radanovic, Christos Dimitrakakis, Debmalya Mandal, and David C Parkes · 2017
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How algorithmic confounding in recommendation systems increases homogeneity and decreases utility
Allison JB Chaney, Brandon M Stewart, and Barbara E Engelhardt · 2018
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Runaway feedback loops in predictive policing
Danielle Ensign, Sorelle A Friedler, Scott Neville, Carlos Scheidegger, and Suresh Venkatasubramanian · 2018
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Addressing function approximation error in actor-critic methods
Scott Fujimoto, Herke Hoof, and David Meger · 2018
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Predictably unequal? The effects of machine learning on credit markets
Andreas Fuster, Paul Goldsmith-Pinkham, Tarun Ramadorai, and Ansgar Walther · 2018
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A short-term intervention for long-term fairness in the labor market
Lily Hu and Yiling Chen · 2018
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Delayed impact of fair machine learning
Lydia T Liu, Sarah Dean, Esther Rolf, Max Simchowitz, and Moritz Hardt · 2018
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On the long-term impact of algorithmic decision policies: Effort unfairness and feature segregation through social learning
Hoda Heidari, Vedant Nanda, and Krishna P. Gummadi · 2019
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The disparate effects of strategic manipulation
Lily Hu, Nicole Immorlica, and Jennifer Wortman Vaughan · 2019
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From fair decision making to social equality
Hussein Mouzannar, Mesrob I Ohannessian, and Nathan Srebro · 2019
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Reinforcement learning with dynamic boltzmann softmax updates
Ling Pan, Qingpeng Cai, Qi Meng, Wei Chen, Longbo Huang, and Tie-Yan Liu · 2019
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Learning in markov decision processes under constraints
Rahul Singh, Abhishek Gupta, and Ness B Shroff · 2020
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How do fair decisions fare in long-term qualification?
Xueru Zhang, Ruibo Tu, Yang Liu, Mingyan Liu, Hedvig Kjellström, Kun Zhang, and Cheng Zhang · 2020
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Constrained upper confidence reinforcement learning
Liyuan Zheng and Lillian Ratliff · 2020
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Modern koopman theory for dynamical systems
Steven L Brunton, Marko Budišić, Eurika Kaiser, and J Nathan Kutz · 2021
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Provably efficient safe exploration via primal-dual policy optimization
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Min Wen, Osbert Bastani, and Ufuk Topcu · 2019
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Dynamic modeling and equilibria in fair decision making
Joshua Williams and J Zico Kolter · 2019
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Constrained episodic reinforcement learning in concave-convex and knapsack settings
Kianté Brantley, Miro Dudik, Thodoris Lykouris, Sobhan Miryoosefi, Max Simchowitz, Aleksandrs Slivkins, and Wen Sun · 2020
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Fairness is not static: Deeper understanding of long term fairness via simulation studies
Alexander D’Amour, Hansa Srinivasan, James Atwood, Pallavi Baljekar, D Sculley, and Yoni Halpern · 2020
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Natural policy gradient primal-dual method for constrained markov decision processes
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Exploration-exploitation in constrained mdps
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A sample-efficient algorithm for episodic finite-horizon mdp with constraints
Krishna C Kalagarla, Rahul Jain, and Pierluigi Nuzzo · 2021
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Learning policies with zero or bounded constraint violation for constrained mdps
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Unintended selection: Persistent qualification rate disparities and interventions
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Stable-baselines3: Reliable reinforcement learning implementations
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Bandit learning with delayed impact of actions
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Crpo: A new approach for safe reinforcement learning with convergence guarantee
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Achieving zero constraint violation for constrained reinforcement learning via primal-dual approach
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Fairness transferability subject to bounded distribution shift
Yatong Chen, Reilly Raab, Jialu Wang, and Yang Liu · 2022
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Provably efficient model-free constrained rl with linear function approximation
Arnob Ghosh, Xingyu Zhou, and Ness Shroff · 2022
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Triple-q: A model-free algorithm for constrained reinforcement learning with sublinear regret and zero constraint violation
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