logo
CanyamAI summaries for academic research
language
MobileMobile
  • Phone FeatureWeChat Mini Program
EnglishEnglish
noticeNotice
BlogBlog
delete
arrow
Return

An incremental randomized algorithm for singular value decomposition of streaming data matrices

delete2025-11-06
delete0
PRE
AI
Y
Yonghe Liu
F
Fengsheng Wu *
B
B. Yu
C
Chaoqian Li
DOI：10.1016/j.aml.2025.109822delete
deleteOriginal
deleteOriginal request for help
deleteShare
deleteSave
Abstract

Abstract

En 中文
Based on the incremental nature of streaming data and the fast computation of randomized projection algorithms, we propose an incremental randomized algorithm for singular value decomposition (IRSVD) to process streaming data matrices quickly and effectively. The computational complexity of IRSVD is discussed, and the error analysis of IRSVD is provided. Numerical experiments on synthetic data and the recommender system demonstrate the superiority of IRSVD in terms of computational cost.

Journal

Applied Mathematics Letters cover
Applied Mathematics Letters
IF:
2.8
Papers:
466
Citations:
1.1W

Organization

No organization information available