Rethinking Resource Management in Edge Learning: A Joint Pre-training and Fine-tuning Design Paradigm

arXiv:2404.00836v1 Announce Type: cross
Abstract: In some applications, edge learning is experiencing a shift in focusing from conventional learning from scratch to new two-stage learning unifying pre-training and task-specific fine-tuning. This paper considers the problem of joint communication and computation resource management in a two-stage edge learning system. In this system, model pre-training is first conducted at an edge server via centralized learning on local pre-stored general data, and then task-specific fine-tuning is performed at edge devices based on the …

abstract applications arxiv communication computation cs.dc cs.it cs.lg design edge fine-tuning management math.it paper paradigm pre-training resource management scratch shift stage training type