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#1
Introduction
#2
Nick Diakopoulos Algorithmic Accountability and Transparency in Journalism
#3
Sara Hajian Discrimination- and Privacy-Aware Data Mining
#4
Toshihiro Kamishima and Kazuto Fukuchi Future Directions of Fairness-Aware Data Mining: Recommendation, Causality, and Theoretical Aspects
#5
Muhammad Bilal Zafar, Isabel Valera Martinez, Manuel Gomez Rodriguez, and Krishna Gummadi Fairness Constraints: A Mechanism for Fair Classification
#6
Indre Zliobaite On the Relation between Accuracy and Fairness in Binary Classification
#7
Fernando Diaz, Sorelle Friedler, Mykola Pechenizkiy, Hanna Wallach, and Suresh Venkatasubramanian (Moderator) A Closing Panel Discussion
#8
Salvatore Ruggieri Privacy Attacks and Anonymization Methods as Tools for Discrimination Discovery and Fairness
#9
Benjamin Fish, Jeremy Kun, and Adam D. Lelkes Fair Boosting: A Case Study
#10
Zubin Jelveh and Michael Luca Towards Diagnosing Accuracy Loss in Discrimination-Aware Classification: An Application to Predictive Policing
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