Fast AI Model Partition for Split Learning over Edge Networks

arXiv:2507.01041v4 Announce Type: replace-cross Abstract: Split learning (SL) is a distributed learning paradigm that can enable computation-intensive artificial intelligence (AI) applications by partitioning AI models between mobile devices and edge servers. %fully utilizing distributed computing resources for computation-intensive mobile intelligence applications. However, the model partitioning problem in SL becomes challenging due to the diverse and complex architectures of AI models. In thi