A Note on Discriminator Updating Method based on Weights of Other Models and its Verification

Abstract

Mobile edge computing has been introduced in various fields. The discriminator of the edge device needs to work for local optimized problems. However, since the edge devices are worked in limited areas, these cannot obtain novel learning data by themselves. Therefore these discriminators need to update by using the knowledge of other devices. Thus, in this paper, a method of updating models using weights of the Neural Networks by transferring and fitting is proposed. It is expected models can be updated for solving local optimized problems for sharing the knowledge of another model that are effective for learning.