Hongyu Zhang

LSTM-AdaPQFL: adaptive compression for hierarchical federated learning

An adaptive model compression method, LSTM-AdaPQFL, which dynamically adjusts compression ratios based on predicted bandwidth, gradient information, and training progress, which offers a novel approach to integrating adaptive model compression into hierarchical FL, advancing privacy‐preserving and communication‐efficient distributed learning.