公开(公告)号：US20220076121A1

公开(公告)日：2022-03-10

申请号：US17153282

申请日：2021-01-20

Applicant: SAMSUNG ELECTRONICS CO., LTD.

Inventor： Saerom CHOI

IPC: G06N3/08 ,  G06N3/04 ,  G06F11/34 ,  G06N3/063

Abstract: A processor-implemented neural architecture search method includes: acquiring performance of neural network blocks included in a pre-trained neural network; selecting at least one target block for performance improvement from the neural network blocks; training weights and architecture parameters of candidate blocks corresponding to the target block based on arbitrary input data and output data of the target block generated based on the input data; and updating the pre-trained neural network by replacing the target block in the pre-trained neural network with one of the candidate blocks based on the trained architecture parameters.

公开(公告)号：US20220108180A1

公开(公告)日：2022-04-07

申请号：US17191954

申请日：2021-03-04

Applicant: Samsung Electronics Co., Ltd.

Inventor： Minkyoung CHO ,  Saerom CHOI ,  Seungwon LEE

IPC: G06N3/08

Abstract: A method and apparatus for compressing an artificial neural network may acquire weights corresponding to an artificial neural network trained in advance, wherein the artificial neural network includes a plurality of layers, and a processor configured to generate data for acquiring a change of behavior of the artificial neural network due to pruning of the artificial neural network based on the weights, determine a pruning threshold for pruning of the artificial neural network based on the change of the behavior of the artificial neural network, and compress the neural network based on the pruning threshold.