Universidade Zambeze

Data and channel-aware device selection for split learning in resource-constrained B5G/6 G networks

Abstract Split learning (SL) is a promising distributed learning approach for fifth-generation/sixth-generation (B5G/6 G) networks. However, its performance is affected by bandwidth constraints and statistical heterogeneity in the data. Prior works have considered either channel-...