SL-FAC reduces communication in split learning via frequency-aware compression of activations and gradients while aiming to preserve training-critical information.
Efficient multi- user resource allocation for urban vehicular edge computing: a hybrid architecture matching approach,
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SL-FAC: A Communication-Efficient Split Learning Framework with Frequency-Aware Compression
SL-FAC reduces communication in split learning via frequency-aware compression of activations and gradients while aiming to preserve training-critical information.