Flexibly Fair Representation Learning by Disentanglement
international conference on machine learning, 2019.
We consider the problem of learning representations that achieve group and subgroup fairness with respect to multiple sensitive attributes. Taking inspiration from the disentangled representation learning literature, we propose an algorithm for learning compact representations of datasets that are useful for reconstruction and predictio...More
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