About this document
Federated Unlearning: Challenges & Methods by Bakary Dolo is a document available to read on EtoBox.
This survey explores federated unlearning (FU), a method for removing identifiable information in federated learning (FL) settings, addressing challenges and techniques for ensuring data privacy. It evaluates existing FU algorithms, presents a unified workflow, and discusses optimizations tailored to federated learning, while highlighting limitations and future research directions. The study emphasizes the importance of maintaining model performance, efficiency, and privacy during the unlearning process.
- Author
- Bakary Dolo
- Language
- EN