Original paper
Optimized Pre-Processing for Discrimination Prevention
Abstract
Non-discrimination is a recognized objective in algorithmic decision making. In this paper, we introduce a novel probabilistic formulation of data pre-processing for reducing discrimination. We propose a convex optimization for learning a data transformation with three goals: controlling discrimination, limiting distortion in individual data samples, and preserving utility. We characterize the impact of limited sample size in accomplishing this...
Paper Details
Title
Optimized Pre-Processing for Discrimination Prevention
Published Date
Jan 1, 2017
Volume
30
Pages
3992 - 4001
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