Improving Fairness and Privacy in Selection Problems.

[2012.03812] Improving Fairness and Privacy in Selection Problems

In this work, we study the possibility of using a differentially private exponential mechanism as a post-processing step to improve both fairness and privacy.

Improving Fairness and Privacy in Selection Problems

Improving Fairness and Privacy in Selection Problems. Mohammad Mahdi Khalili,1 Xueru Zhang, 2 Mahed Abroshan, 3 Somayeh Sojoudi 4. 1 CIS Department ...

Improving Fairness and Privacy in Selection Problems | Request PDF

Among various privacy notions, differential privacy has become popular in recent years. In this work, we study the possibility of using a differentially private ...

[PDF] Improving Fairness and Privacy in Selection Problems

This work studies the possibility of using a differentially private exponential mechanism as a post-processing step to improve both fairness ...

(PDF) Improving Fairness and Privacy in Selection Problems

Jagielski et al. ... parity in the appendix. ... attributes but without a privacy guarantee. ... all the applicants as long as they are likely to be ...

Improving Fairness and Privacy in Selection Problems. - DBLP

To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them ...

Privacy, accuracy, and model fairness trade-offs in federated learning

Our study also shows that privacy can come at the cost of fairness, as stricter privacy can intensify discrimination. Hence, we posit that careful parameter ...

Fairness in Selection Problems with Strategic Candidates

Our results reveal important impacts of the strategic behavior on the discrimination observed at equilibrium and allow us to understand the ...

Fairness issues, current approaches, and challenges in machine ...

With the increasing influence of machine learning algorithms in decision-making processes, concerns about fairness have gained significant ...

On fair selection in the presence of implicit and differential variance

Discrimination in selection problems such as hiring or college admission is often explained by implicit bias from the decision maker against disadvantaged ...

Learning Fair Policies for Multi-Stage Selection Problems from ...

Improving fairness and privacy in selection problems. In Proceedings of the AAAI Conference on Artificial Intelli- gence, volume 35(9), 8092–8100. Kilbertus ...

Strategies to improve fairness in artificial intelligence:A systematic ...

Generally, techniques to promote fairness can be implemented in the following stages of the AI process: preprocessing, processing (also ...

Differential Privacy and Fairness in Decisions and Learning Tasks

processing bias mitigation solutions to improve fairness with- out affecting data privacy. ... Improv- ing fairness and privacy in selection problems. In Thirty-.

Examining the Interplay Between Privacy and Fairness for Speech ...

Sojoudi, “Improv- ing fairness and privacy in selection problems,” in Proceedings ... Walker, “Fairlearn: A toolkit for assessing and improving ...

On the Duality of Privacy and Fairness - HAL

Improving fairness and privacy in selection problems. Proc. of the 35th. AAAI Conference on Artificial Intelligence (AAAI 2021),. 35:8092–8100 ...

Imposing Fairness Constraints in Synthetic Data Generation

Improving fairness and privacy in selection problems. In Proceedings of the ... fairness in learning: Feature selection for fair decision making. In ...

Fairness and Privacy in Machine Learning - Michaël Perrot

Fairness and Privacy have been extensively studied as individual constraints. ... Improving fairness and privacy in selection problems. arXiv e-prints, pages ...

Increasing Fairness in Machine Learning Systems - Amplitude

The simplest approach to removing bias against certain demographics is to simply remove the protected attribute (e.g. race, gender, etc) as an ...

Differential Privacy and Fairness in Decisions and Learning Tasks

The survey reviews the conditions under which privacy and fairness may be aligned or contrasting goals, analyzes how and why DP exacerbates bias and ...

Improving fairness generalization through a sample-robust ...

A common solution to mitigate it is to integrate and optimize a statistical fairness metric along with accuracy during the training phase.