arXiv CS
open access
Unsupervised Head Network Personalization for Split Computing via Federated Learning
Split Computing (SC) is a distributed inference method designed for balancing computational load and reducing latency by partitioning a neural network into head and tail networks and deploying them across both a mobile device and a server, respectively. Due to the limited bandwidth and computational
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