FairDP: Certified Fairness with Differential Privacy
- URL: http://arxiv.org/abs/2305.16474v2
- Date: Mon, 21 Aug 2023 20:09:24 GMT
- Title: FairDP: Certified Fairness with Differential Privacy
- Authors: Khang Tran, Ferdinando Fioretto, Issa Khalil, My T. Thai, NhatHai Phan
- Abstract summary: This paper introduces FairDP, a novel mechanism designed to achieve certified fairness with differential privacy (DP)
FairDP independently trains models for distinct individual groups, using group-specific clipping terms to assess and bound the disparate impacts of DP.
Extensive theoretical and empirical analyses validate the efficacy of FairDP and improved trade-offs between model utility, privacy, and fairness compared with existing methods.
- Score: 59.56441077684935
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: This paper introduces FairDP, a novel mechanism designed to achieve certified
fairness with differential privacy (DP). FairDP independently trains models for
distinct individual groups, using group-specific clipping terms to assess and
bound the disparate impacts of DP. Throughout the training process, the
mechanism progressively integrates knowledge from group models to formulate a
comprehensive model that balances privacy, utility, and fairness in downstream
tasks. Extensive theoretical and empirical analyses validate the efficacy of
FairDP and improved trade-offs between model utility, privacy, and fairness
compared with existing methods.
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