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Proximal Alternating-Direction-Method-of-Multipliers-Incorporated Nonnegative Latent Factor Analysis

Fanghui Bi Xin Luo Bo Shen Hongli Dong Zidong Wang

自动化学报（英文版）2023，Vol.10Issue(6)：1388-1406,19.

自动化学报（英文版）2023，Vol.10Issue(6)：1388-1406,19.DOI:10.1109/JAS.2023.123474

Proximal Alternating-Direction-Method-of-Multipliers-Incorporated Nonnegative Latent Factor Analysis

Fanghui Bi ¹Xin Luo ²Bo Shen ³Hongli Dong ⁴Zidong Wang⁵

作者信息

1. Chongqing Institute of Green and Intelligent Technology,Chinese Academy of Sciences,Chongqing School,University of Chinese Academy of Sciences,Chongqing 400714,China
2. College of Computer and Information Science,Southwest University,Chongqing 400715,China
3. College of Information Science and Technology,Donghua University,Shanghai 201620,China
4. Artificial Intelligence Energy Research Institute,Northeast Petroleum University,Daqing 163318,China
5. Department of Computer Science,Brunel University London,Uxbridge UB83PH,United Kingdom
折叠

摘要

关键词

Data science/high-dimensional and incomplete data/knowledge acquisition/industrial application/nonnegative latent fac-tor analysis(NLFA)/proximal alternating direction method of multi-pliers/representation learning

Key words

引用本文复制引用

Fanghui Bi,Xin Luo,Bo Shen,Hongli Dong,Zidong Wang..Proximal Alternating-Direction-Method-of-Multipliers-Incorporated Nonnegative Latent Factor Analysis[J].自动化学报（英文版）,2023,10(6):1388-1406,19.

基金项目

This work was supported by the National Natural Science Foundation of China(62272078,U21A2019),the Hainan Province Science and Technology Special Fund of China(ZDYF2022SHFZ105),and the CAAI-Huawei MindSpore Open Fund(CAAIXSJLJJ-2021-035A). （62272078,U21A2019）

自动化学报（英文版）

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