Fetching the paper…
Reading the bibliography…
The rise of algorithmic decision making led to active researches on how to define and guarantee fairness, mostly focusing on one-shot decision making.
Multi-stage classification
Ted E. Senator · 2005
Earlier work this paper cites.
Discrimination-aware data mining
Dino Pedreshi, Salvatore Ruggieri, and Franco Turini · 2008
Earlier work this paper cites.
Fairness through awareness
Cynthia Dwork, Moritz Hardt, Toniann Pitassi, Omer Reingold, and Richard Zemel · 2012
Earlier work this paper cites.
Multi-stage classifier design
Kirill Trapeznikov, Venkatesh Saligrama, and David Castañón · 2012
Earlier work this paper cites.
Predictive Policing: The Role of Crime Forecasting in Law Enforcement Operations
Walter L. Perry, Brian McInnis, Carter C. Price, Susan C. Smith, and John S. Hollywood · 2013
Earlier work this paper cites.
An Introduction to Probability and Statistics
Vijay K. Rohatgi and A.K.M.E. Saleh · 2015
Earlier work this paper cites.
Equality of opportunity in supervised learning
Moritz Hardt, Eric Price, and Nathan Srebro · 2016
Earlier work this paper cites.
Fairness in learning: Classic and contextual bandits
Matthew Joseph, Michael Kearns, Jamie Morgenstern, and Aaron Roth · 2016
Earlier work this paper cites.
How We Analyzed the COMPAS Recidivism Algorithm, 2016
Jeff Larson, Surya Mattu, Lauren Kirchner, and Julia Angwin · 2016
Cited alongside, same era.
Fair pipelines
Amanda Bower, Sarah N. Kitchen, Laura Niss, Martin J. Strauss, Alex Vargo, and Suresh Venkatasubramanian · 2017
Cited alongside, same era.
Fair prediction with disparate impact: A study of bias in recidivism prediction instruments
Alexandra Chouldechova · 2017
Cited alongside, same era.
Algorithmic decision making and the cost of fairness
Sam Corbett-Davies, Emma Pierson, Avi Feller, Sharad Goel, and Aziz Huq · 2017
Cited alongside, same era.
UCI machine learning repository, 2017
Dheeru Dua and Casey Graff · 2017
Cited alongside, same era.
Fairness in reinforcement learning
Shahin Jabbari, Matthew Joseph, Michael Kearns, Jamie Morgenstern, and Aaron Roth · 2017
Cited alongside, same era.
Fairness beyond disparate treatment & disparate impact: Learning classification without disparate mistreatment
Muhammad Bilal Zafar, Isabel Valera, Manuel Gomez Rodriguez, and Krishna P. Gummadi · 2017
Later among the works it cites.
Preventing disparate treatment in sequential decision making
Hoda Heidari and Andreas Krause · 2018
Later among the works it cites.
Selection problems in the presence of implicit bias
Jon Kleinberg and Manish Raghavan · 2018
Later among the works it cites.
Algorithmic bias? an empirical study into apparent gender-based discrimination in the display of stem career ads, March 2018
Anja Lambrecht and E. Tucker, Catherine · 2018
Later among the works it cites.
Does mitigating ml’s impact disparity require treatment disparity?
Zachary Lipton, Julian McAuley, and Alexandra Chouldechova · 2018
Later among the works it cites.
Enhancing the accuracy and fairness of human decision making
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Avoiding discrimination through causal reasoning
Niki Kilbertus, Mateo Rojas Carulla, Giambattista Parascandolo, Moritz Hardt, Dominik Janzing, and Bernhard Schölkopf · 2017
Cited alongside, same era.
Inherent trade-offs in the fair determination of risk scores
Jon Kleinberg, Sendhil Mullainathan, and Manish Raghavan · 2017
Cited alongside, same era.
Isabel Valera, Adish Singla, and Manuel Gomez Rodriguez · 2018
Later among the works it cites.
Fairness under composition
Cynthia Dwork and Christina Ilvento · 2019
Closest in time.
The diverse cohort selection problem
Candice Schumann, Samsara N. Counts, Jeffrey S. Foster, and John P. Dickerson · 2019
Closest in time.