Package for evaluating the performance of methods which aim to increase fairness, accountability and/or transparency
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Updated
Jun 24, 2024 - Python
Package for evaluating the performance of methods which aim to increase fairness, accountability and/or transparency
Official implementation of our work "Collaborative Fairness in Federated Learning."
A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitigate bias in datasets and models.
Toolkit for Auditing and Mitigating Bias and Fairness of Machine Learning Systems 🔎🤖🧰
Learning Fair Representations for Recommendation: A Graph-based Perspective, WWW2021
Fairness-aware Data Mining
Package implementing methods developed in "Preventing Fairness Gerrymandering" [ICML '18], "Rich Subgroup Fairness for Machine Learning" [ FAT* '19]. active development fork @algowatchupenn
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