公开(公告)号：US20230098672A1

公开(公告)日：2023-03-30

申请号：US17574501

申请日：2022-01-12

Applicant: Korea Advanced Institute of Science and Technology

Inventor： Hoi Jun YOO ,  So Yeon KIM

IPC: G06N3/08 ,  G06V10/82 ,  G06V10/776

Abstract: Disclosed is an energy-efficient retraining method of a generative neural network for domain-specific optimization, including (a) retraining, by a mobile device, a pretrained generative neural network model with respect to some data of a new user dataset, (b) comparing, by the mobile device, the pretrained generative neural network model and a generative neural network model retrained for each layer with each other in terms of a relative change rate of weights, (c) selecting, by the mobile device, specific layers having high relative change rate of weights, among layers of the pretrained generative neural network model, as layers to be retrained, and (d) performing, by the mobile device, weight update for only the layers selected in step (c), wherein only some of all layers are selected and trained in a retraining process that requires a large amount of operation, whereby rapid retraining is performed in the mobile device.