期刊论文

Lim, Se-Jung

英文

计算机、材料和连续体(英文)

1546-2218

2020

62

1

321-336

10.32604/cmc.2020.06130

This work was supported by National Natural Science Foundation of China (Nos. 61802030, 61572184), the Science and Technology Projects of Hunan Province (No. 2016JC2075), the International Cooperative Project for ?Double First-Class?, CSUST (No. 2018IC24).

本校为第一机构

With the popularity of deep learning tools in image decomposition and natural language processing, how to support and store a large number of parameters required by deep learning algorithms has become an urgent problem to be solved. These parameters are huge and can be as many as millions. At present, a feasible direction is to use the sparse representation technique to compress the parameter matrix to achieve the purpose of reducing parameters and reducing the storage pressure. These methods include matrix decomposition and tensor decompositio...