A Multivocal Literature Review on Privacy and Fairness in Federated Learning
B Balbierer, L Heinlein, D Zipperling, N Kühl - ar** Federated Graph Neural Networks with Structure-aware Group Fairness
Graph Neural Networks (GNNs) are used for graph data processing across various domains.
Centralized training of GNNs often faces challenges due to privacy and regulatory issues …
Centralized training of GNNs often faces challenges due to privacy and regulatory issues …
Linkage on Security, Privacy and Fairness in Federated Learning: New Balances and New Perspectives
Federated learning is fast becoming a popular paradigm for applications involving mobile
devices, banking systems, healthcare, and IoT systems. Hence, over the past five years …
devices, banking systems, healthcare, and IoT systems. Hence, over the past five years …
WassFFed: Wasserstein Fair Federated Learning
Z Han, L Zhang, C Chen, X Zheng, F Zheng… - arxiv preprint arxiv …, 2024 - arxiv.org
Federated Learning (FL) employs a training approach to address scenarios where users'
data cannot be shared across clients. Achieving fairness in FL is imperative since training …
data cannot be shared across clients. Achieving fairness in FL is imperative since training …
Adaptive Homogeneity-Based Client Selection Policy for Federated Learning
Federated learning (FL) is a distributed paradigm that enables multiple clients or edge
devices to collaboratively train a model without sharing their local data. The FL system has …
devices to collaboratively train a model without sharing their local data. The FL system has …
[PDF][PDF] Addressing Bias and Fairness using Fair Federated Learning: A Systematic
D Kim, H Woo, Y Lee - 2024 - preprints.org
In the field of machine learning, the rapid development of data volume and variety requires
ethical data utilization and strict privacy protection standards. Fair Federated Learning (FFL) …
ethical data utilization and strict privacy protection standards. Fair Federated Learning (FFL) …
[PDF][PDF] Challenges in Algorithmic Fairness when using Multi-Party Computation Models
C Wibaut, V Dunning, MB van Egmond - bnaic2024.sites.uu.nl
While the topics of Secure Multi-Party Computation (MPC) and Algorithmic Fairness (or in
short, fairness) are essential in the area of Responsible AI, they are typically researched …
short, fairness) are essential in the area of Responsible AI, they are typically researched …