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Automated Feature Engineering for Algorithmic Fairness

Summary: Automated feature engineering via multi-objective optimization to jointly maximize accuracy and fairness in ML models. Vertical fairness via feature construction avoids data tampering, delivering higher accuracy and comparable or better fairness than Capuchin on three datasets. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
12355
Venue
VLDB
Year
2021
Pagerank
5.934329e-05
Overall Rank
4,769 | 66.83%
DOI
10.14778/3461535.3463474

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