Fed-QSSL: A Framework for Personalized Federated Learning under Bitwidth and Data Heterogeneity

1 code implementation • 20 Dec 2023 • Yiyue Chen, Haris Vikalo, Chianing Wang

Motivated by high resource costs of centralized machine learning schemes as well as data privacy concerns, federated learning (FL) emerged as an efficient alternative that relies on aggregating locally trained models rather than collecting clients' potentially private data.

Personalized Federated Learning Quantization +1