Symmetric generalized low rank approximations of matrices

Kohei Inoue, Hara Kenji, Kiichi Urahama

研究成果: Chapter in Book/Report/Conference proceedingConference contribution

3 引用 (Scopus)

抜粋

Recently, the generalized low rank approximations of matrices (GLRAM) have been proposed for dimensionality reduction of matrices such as images. However, in GLRAM, it is necessary for users to specify the numbers of rows and columns in low rank matrices. In this paper, we propose a method for determining them semiautomatically by symmetrizing GLRAM. Experimental results show that the proposed method can determine the optimal ranks of matrices while achieving competitive approximation performance.

元の言語英語
ホスト出版物のタイトル2012 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2012 - Proceedings
ページ949-952
ページ数4
DOI
出版物ステータス出版済み - 2012
イベント2012 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2012 - Kyoto, 日本
継続期間: 3 25 20123 30 2012

その他

その他2012 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2012
日本
Kyoto
期間3/25/123/30/12

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Software
  • Electrical and Electronic Engineering

これを引用

Inoue, K., Kenji, H., & Urahama, K. (2012). Symmetric generalized low rank approximations of matrices. : 2012 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2012 - Proceedings (pp. 949-952). [6288042] https://doi.org/10.1109/ICASSP.2012.6288042