Feras M. Awaysheh

FedSparQ: Adaptive Sparse Quantization with Error Feedback for Robust & Efficient Federated Learning

2025 · arXiv (Cornell University)

Federated Learning (FL) enables collaborative model training across decentralized clients while preserving data privacy by keeping raw data local. However, FL suffers from significant communication overhead due to the frequent exchange of high-dimensional model updates …