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.
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页码：908 / 920
页数：12
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