A latency-driven scheduler jointly tunes activation compression and synchronization frequency in federated split learning, delivering up to 87% payload reduction and 54% less synchronization traffic on rainfall prediction with AUPRC change under 0.011.
Splitfedzip: Learned compression for data transfer reduction in split-federated learning,
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Adaptive Joint Compression and Synchronisation in Federated Split Learning for IoT Rainfall Prediction
A latency-driven scheduler jointly tunes activation compression and synchronization frequency in federated split learning, delivering up to 87% payload reduction and 54% less synchronization traffic on rainfall prediction with AUPRC change under 0.011.