From Parity to Preference-based Notions of Fairness in ClassificationMuhammad Bilal Zafar, Isabel Valera, Manuel Gomez Rodriguez, Krishna P. Gummadi and Adrian Weller
Racial Disparity in Natural Language Processing: A Case Study of Social Media African-American EnglishSu Lin Blodgett and Brendan O'Connor
Fair Clustering Through FairletsFlavio Chierichetti, Ravi Kumar, Silvio Lattanzi and Sergei Vassilvitskii
Runaway Feedback Loops in Predictive PolicingDanielle Ensign, Sorelle A. Friedler, Scott Neville, Carlos Scheidegger and Suresh Venkatasubramanian
Fairness at Equilibrium in the Labor MarketLily Hu and Yiling Chen
Calibrated fairness in banditsYang Liu, Goran Radanovic, Christos Dimitrakakis, David Parkes and Debmalya Mandal
The Authority of "Fair" in Machine LearningMichael Skirpan and Micha Gorelick
Logics and practices of transparency and opacity in real-world applications of public sector machine learningMichael Veale
A reductions approach to fair classificationAlekh Agarwal, Alina Beygelzimer, Miroslav Dudik and John Langford
Interpretability via Model ExtractionOsbert Bastani, Carolyn Kim and Hamsa Bastani
Learning Fair Classifiers: A Regularization ApproachYahav Bechavod and Katrina Ligett
A Convex Framework for Fair RegressionRichard Berk, Hoda Heidari, Shahin Jabbari, Matthew Joseph, Michael Kearns, Jamie Morgenstern, Seth Neel and Aaron Roth
Data Decisions and Theoretical Implications when Adversarially Learning Fair RepresentationsAlex Beutel, Jilin Chen, Zhe Zhao and Ed H. Chi
Fair PipelinesAmanda Bower, Sarah Kitchen, Laura Niss, Martin Strauss, Alexander Vargo and Suresh Venkatasubramanian
Multisided Fairness for RecommendationRobin Burke
Fair PersonalizationL. Elisa Celis and Nisheeth Vishnoi
Fairer and more accurate, but for whom?Alexandra Chouldechova and Max G'Sell
Decoupled classifiers for fair and efficient MLCynthia Dwork, Nicole Immorlica, Adam Kalai and Max Leiserson
Decision making with limited feedback: Error bounds for recidivism prediction and predictive policingDanielle Ensign, Sorelle Friedler, Scott Neville, Carlos Scheidegger and Suresh Venkatasubramanian
Is it ethical to avoid error analysis?Eva García-Martín and Niklas Lavesson
On Fairness, Diversity and Randomness in Algorithmic Decision MakingNina Grgic-Hlaca, Muhammad Bilal Zafar, Krishna P. Gummadi and Adrian Weller
Better Fair Algorithms for Contextual BanditsMatthew Joseph, Michael Kearns, Jamie Morgenstern, Seth Neel and Aaron Roth
Fair Algorithms for Infinite Contextual BanditsMatthew Joseph, Michael Kearns, Jamie Morgenstern, Seth Neel and Aaron Roth
Interpretable & Explorable Approximations of Black Box ModelsHimabindu Lakkaraju, Ece Kamar, Rich Caruana and Jure Leskovec
Discriminatory TransferChao Lan and Jun Huan
The causal impact of bail on case outcomes for indigent defendantsKristian Lum and Mike Baiocchi
Causal Falling Rule ListsFulton Wang and Cynthia Rudin
New Fairness Metrics for Recommendation that Embrace DifferencesSirui Yao and Bert Huang
Identifying Significant Predictive Bias in ClassifiersZhe Zhang and Daniel Neill