| Proportional Fairness in Federated Learning | Feb 3, 2022 | FairnessFederated Learning | CodeCode Available | 1 |
| Net benefit, calibration, threshold selection, and training objectives for algorithmic fairness in healthcare | Feb 3, 2022 | Decision MakingFairness | CodeCode Available | 0 |
| FORML: Learning to Reweight Data for Fairness | Feb 3, 2022 | Fairnessimage-classification | —Unverified | 0 |
| Normalise for Fairness: A Simple Normalisation Technique for Fairness in Regression Machine Learning Problems | Feb 2, 2022 | Binary ClassificationDecision Making | —Unverified | 0 |
| Fairness of Machine Learning Algorithms in Demography | Feb 2, 2022 | BIG-bench Machine LearningFairness | —Unverified | 0 |
| Diagnosing failures of fairness transfer across distribution shift in real-world medical settings | Feb 2, 2022 | BIG-bench Machine LearningFairness | —Unverified | 0 |
| An Empirical Study of Modular Bias Mitigators and Ensembles | Feb 1, 2022 | Ensemble LearningFairness | —Unverified | 0 |
| Achieving Fairness at No Utility Cost via Data Reweighing with Influence | Feb 1, 2022 | BIG-bench Machine LearningFairness | CodeCode Available | 1 |
| Federated Active Learning (F-AL): an Efficient Annotation Strategy for Federated Learning | Feb 1, 2022 | Active LearningDistributed Optimization | —Unverified | 0 |
| Learning Fair Representations via Rate-Distortion Maximization | Jan 31, 2022 | AttributeFairness | CodeCode Available | 0 |
