KINDER: Kernel-based independence for fair representation learning via prototype-space erasure
Read the original at arxiv.org→arXiv:2611.00264v1 Announce Type: new Abstract: Concept erasure is a prominent approach to achieving fairness in machine learning through the removal of sensitive attributes from learned representations. Prior...
Original headline: "KINDER: Kernel-based Independence for Fair Representation Learning via Prototype-space Erasure"
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- Nov 3, 05:00 UTC arXiv cs.LG lead source KINDER: Kernel-based Independence for Fair Representation Learning via Prototype-space Erasure