Individual fairness guarantees for neural networks
We consider the problem of certifying the individual fairness (IF) of feed-forward neural networks (NNs). In particular, we work with the epsilon-delta-IF formulation, which, given a NN and a similarity metric learnt from data, requires that the output difference between any pair of epsilon-similar...
| Main Authors: | , , , , |
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| Format: | Conference item |
| Language: | English |
| Published: |
International Joint Conferences on Artificial Intelligence
2022
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