A State-Migration Particle Swarm Optimizer for Adaptive Latent Factor Analysis of High-Dimensional and Incomplete Data
文献类型：期刊论文
| 作者 | Jiufang Chen; Kechen Liu; Xin Luo; Ye Yuan; Khaled Sedraoui; Yusuf Al-Turki; MengChu Zhou |
| 刊名 | IEEE/CAA Journal of Automatica Sinica
 |
| 出版日期 | 2024 |
| 卷号 | 11期号:11页码:2220-2235 |
| 关键词 | Data science generalized momentum high-dimensional and incomplete (HDI) data hyper-parameter adaptation latent factor analysis (LFA) particle swarm optimization (PSO) |
| ISSN号 | 2329-9266 |
| DOI | 10.1109/JAS.2024.124575 |
| 英文摘要 | High-dimensional and incomplete (HDI) matrices are primarily generated in all kinds of big-data-related practical applications. A latent factor analysis (LFA) model is capable of conducting efficient representation learning to an HDI matrix, whose hyper-parameter adaptation can be implemented through a particle swarm optimizer (PSO) to meet scalable requirements. However, conventional PSO is limited by its premature issues, which leads to the accuracy loss of a resultant LFA model. To address this thorny issue, this study merges the information of each particle’s state migration into its evolution process following the principle of a generalized momentum method for improving its search ability, thereby building a state-migration particle swarm optimizer (SPSO), whose theoretical convergence is rigorously proved in this study. It is then incorporated into an LFA model for implementing efficient hyper-parameter adaptation without accuracy loss. Experiments on six HDI matrices indicate that an SPSO-incorporated LFA model outperforms state-of-the-art LFA models in terms of prediction accuracy for missing data of an HDI matrix with competitive computational efficiency. Hence, SPSO’s use ensures efficient and reliable hyper-parameter adaptation in an LFA model, thus ensuring practicality and accurate representation learning for HDI matrices. |
| 源URL | [http://ir.ia.ac.cn/handle/173211/59449]  |
| 专题 | 自动化研究所_学术期刊_IEEE/CAA Journal of Automatica Sinica |
| 推荐引用方式 GB/T 7714 | Jiufang Chen,Kechen Liu,Xin Luo,et al. A State-Migration Particle Swarm Optimizer for Adaptive Latent Factor Analysis of High-Dimensional and Incomplete Data[J]. IEEE/CAA Journal of Automatica Sinica,2024,11(11):2220-2235. |
| APA | Jiufang Chen.,Kechen Liu.,Xin Luo.,Ye Yuan.,Khaled Sedraoui.,...&MengChu Zhou.(2024).A State-Migration Particle Swarm Optimizer for Adaptive Latent Factor Analysis of High-Dimensional and Incomplete Data.IEEE/CAA Journal of Automatica Sinica,11(11),2220-2235. |
| MLA | Jiufang Chen,et al."A State-Migration Particle Swarm Optimizer for Adaptive Latent Factor Analysis of High-Dimensional and Incomplete Data".IEEE/CAA Journal of Automatica Sinica 11.11(2024):2220-2235. |
入库方式： OAI收割
来源：自动化研究所
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