HO-FL: Hybrid-Order Federated Learning for Heterogeneous Edge Devices
Federated learning (FL) on memory-constrained edge devices faces a dilemma: first-order (FO) optimization (i.e., backpropagation) demands substantial memory, whereas zeroth-order (ZO) optimization suffers from severe convergence slowdown. To resolve this dilemma, we introduce HO-FL, a hybrid-order FL framework that tra...
Qi-Yuan Chen, Xian Wu, Ya-Nan Ma et al.
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