| Fairness-Driven Private Collaborative Machine Learning | Sep 29, 2021 | BIG-bench Machine LearningFairness | —Unverified | 0 | 0 |
| Fairness in Federated Learning for Spatial-Temporal Applications | Jan 17, 2022 | FairnessFederated Learning | —Unverified | 0 | 0 |
| Fairness in the Eyes of the Data: Certifying Machine-Learning Models | Sep 3, 2020 | BIG-bench Machine LearningFairness | —Unverified | 0 | 0 |
| Fairness Issues and Mitigations in (Differentially Private) Socio-Demographic Data Processes | Aug 16, 2024 | FairnessPrivacy Preserving | —Unverified | 0 | 0 |
| Faithful and Privacy-Preserving Implementation of Average Consensus | Mar 12, 2025 | Privacy Preserving | —Unverified | 0 | 0 |
| Faking feature importance: A cautionary tale on the use of differentially-private synthetic data | Mar 2, 2022 | Feature ImportancePrivacy Preserving | —Unverified | 0 | 0 |
| Fast-adapting and Privacy-preserving Federated Recommender System | Apr 2, 2021 | Federated LearningMeta-Learning | —Unverified | 0 | 0 |
| Fast-Convergent and Communication-Alleviated Heterogeneous Hierarchical Federated Learning in Autonomous Driving | Sep 29, 2024 | Autonomous DrivingFederated Learning | —Unverified | 0 | 0 |
| Fast Deep Autoencoder for Federated learning | Jun 10, 2022 | Anomaly DetectionEdge-computing | —Unverified | 0 | 0 |
| Fast John Ellipsoid Computation with Differential Privacy Optimization | Aug 12, 2024 | Privacy Preserving | —Unverified | 0 | 0 |
