AI RESEARCH
SL-FAC: A Communication-Efficient Split Learning Framework with Frequency-Aware Compression
arXiv CS.LG
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ArXi:2604.07316v1 Announce Type: new The growing complexity of neural networks hinders the deployment of distributed machine learning on resource-constrained devices. Split learning (SL) offers a promising solution by partitioning the large model and offloading the primary