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cs.LG2021
DICE: Deep Significance Clustering for Outcome-Aware Stratification
Yufang Huang, Kelly M. Axsom, John Lee +2
We present deep significance clustering (DICE), a framework for jointly performing representation learning and clustering for "outcome-aware" stratification. DICE is intended to ge…
cs.LG2019★ 4 cited
What is Fair? Exploring Pareto-Efficiency for Fairness Constrained Classifiers
Ananth Balashankar, Alyssa Lees, Chris Welty +1
The potential for learned models to amplify existing societal biases has been broadly recognized. Fairness-aware classifier constraints, which apply equality metrics of performance…