A Scalable and Privacy-Enhanced Federated Learning Framework with Adaptive Trade-offs Between Communication Efficiency, Privacy Guarantees, and Model Performance in Non-IID Environments. InPrime: Indonesian Journal of Pure and Applied Mathematics, [S. l.], v. 7, n. 2, p. 144–158, 2025. DOI: 10.15408/frxdzc84. Disponível em: https://journal.uinjkt.ac.id/inprime/article/view/45035. Acesso em: 20 nov. 2025.