3 citations · 9 across the 6 of their papers we have counts for
5 papers · 1 filter
SoFaiR: Single Shot Fair Representation Learning
Xavier Gitiaux, Huzefa Rangwala
To avoid discriminatory uses of their data, organizations can learn to map them into a representation that filters out information related to sensitive attributes. However, all exi…
Fair Representations by Compression
Xavier Gitiaux, Huzefa Rangwala
Organizations that collect and sell data face increasing scrutiny for the discriminatory use of data. We propose a novel unsupervised approach to transform data into a compressed b…
Learning Smooth and Fair Representations
Xavier Gitiaux, Huzefa Rangwala
Organizations that own data face increasing legal liability for its discriminatory use against protected demographic groups, extending to contractual transactions involving third p…
Probabilistic Super-Resolution of Solar Magnetograms: Generating Many Explanations and Measuring Uncertainties
Xavier Gitiaux, Shane A. Maloney, Anna Jungbluth +7
Machine learning techniques have been successfully applied to super-resolution tasks on natural images where visually pleasing results are sufficient. However in many scientific do…
Multi-Differential Fairness Auditor for Black Box Classifiers
Xavier Gitiaux, Huzefa Rangwala
Machine learning algorithms are increasingly involved in sensitive decision-making process with adversarial implications on individuals. This paper presents mdfa, an approach that…