Efficient fair PCA for fair representation learning

Matthäus Kleindessner, Michele Donini, Chris Russell +1

We revisit the problem of fair principal component analysis (PCA), where the goal is to learn the best low-rank linear approximation of the data that obfuscates demographic informa…