Linear low-rank approximation and nonlinear dimensionality reduction

被引：0
|
作者：
Zhenyue Zhang
Hongyuan Zha
机构：
[1] Zhejiang University,Department of Mathematics
[2] Yuquan Campus,Department of Computer Science and Engineering
[3] The Pennsylvania State University,undefined
来源：
Science in China Series A: Mathematics | 2004年 / 47卷
关键词：
singular value decomposition; low-rank approximation; sparse matrix; nonlinear dimensionality reduction; principal manifold; subspace alignment; data mining;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
We present our recent work on both linear and nonlinear data reduction methods and algorithms: for the linear case we discuss results on structure analysis of SVD of columnpartitioned matrices and sparse low-rank approximation; for the nonlinear case we investigate methods for nonlinear dimensionality reduction and manifold learning. The problems we address have attracted great deal of interest in data mining and machine learning.
引用
收藏
页码：908 / 920
页数：12
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