Preprint
Aug 2026
Adaptive Heterogeneous Compression for Resource-Efficient Federated Knowledge Distillation
A heterogeneous compression framework for FedKD is proposed that enables each client to select a compression strategy from a candidate strategy set, and an Adaptive heterogeneouS Compression algorithm for fEderated kNowledge Distillation (ASCEND), which employs an exponential moving average (EMA)-enhanced $\epsilon$-greedy policy to balance exploration and exploitation.
Chen-Wang Liu, Yijun Liu, Chang Liu et al.
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