Feature Map Compression for Split Learning in Mobile Wireless Environment: Theory and Practice
Split Learning (SL) enables collaborative model training by distributing computation between resource-constrained mobile edge devices and a central server. In this distributed framework, mobile edge devices compute the early layers of the model and transmit feature maps to the server. However, due to practical mobile w...