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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