Federated Learning Economics: Privacy vs Efficiency
Abstract
An economic analysis of federated learning implementations across enterprise AI projects, examining computational overhead, communication costs, regulatory compliance value, and decision frameworks for choosing between centralized and federated approaches.
Fields of Study & Subjects
Privacy-Preserving Technologies in Data
Ethics and Social Impacts of AI
Privacy
Security
and Data Protection
Publication details
- Journal / source
- Zenodo (CERN European Organization for Nuclear Research)
- Publication date
- 16 February 2026
- Language
- EN