Publikation
Learning with privileged and sensitive information: a gradient-boosting approach
Siwen Yan; Phillip Odom; Rahul Pasunuri; Kristian Kersting; Sriraam Natarajan
In: Frontiers in Artificial Intelligence, Vol. 6, Pages 1-11, Frontiers, 2023.
Zusammenfassung
We consider the problem of learning with sensitive features under the privileged
information setting where the goal is to learn a classifier that uses features
not available (or too sensitive to collect) at test/deployment time to learn a
better model at training time. We focus on tree-based learners, specifically
gradient-boosted decision trees for learning with privileged information. Our
methods use privileged features as knowledge to guide the algorithm when
learning from fully observed (usable) features. We derive the theory, empirically
validate the effectiveness of our algorithms, and verify them on standard
fairness metrics.