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- W2811046100 abstract "No methods currently exist for making arbitrary neural networks fair. In this work we introduce GRAD, a new and simplified method to producing fair neural networks that can be used for auto-encoding fair representations or directly with predictive networks. It is easy to implement and add to existing architectures, has only one (insensitive) hyper-parameter, and provides improved individual and group fairness. We use the flexibility of GRAD to demonstrate multi-attribute protection." @default.
- W2811046100 created "2018-07-10" @default.
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- W2811046100 date "2018-07-01" @default.
- W2811046100 modified "2023-09-27" @default.
- W2811046100 title "Gradient Reversal Against Discrimination." @default.
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