ProtoFair uses prototype clustering to form pseudo-counterfactual pairs for an additive fairness contrastive loss that improves fairness metrics on CelebA and UTKFace while preserving accuracy in SimCLR and SupCon.
Journal of Machine Learning Research9, 2579–2605 (2008) 13
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ProtoFair: Fair Self-Supervised Contrastive Learning via Pseudo-Counterfactual Pairs
ProtoFair uses prototype clustering to form pseudo-counterfactual pairs for an additive fairness contrastive loss that improves fairness metrics on CelebA and UTKFace while preserving accuracy in SimCLR and SupCon.