54 search results - page 9 / 11 » Semi-supervised learning by locally linear embedding in kern... |
102
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SIGMOD
2010
ACM
15 years 2 months ago
2010
ACM
Similarity search methods are widely used as kernels in various data mining and machine learning applications including those in computational biology, web search/clustering. Near...
100
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MM
2006
ACM
15 years 3 months ago
2006
ACM
In many image retrieval applications, the mapping between highlevel semantic concept and low-level features is obtained through a learning process. Traditional approaches often as...
ICCV
2007
IEEE
15 years 3 months ago
2007
IEEE
Dimensionality reduction plays a fundamental role in data processing, for which principal component analysis (PCA) is widely used. In this paper, we develop the Laplacian PCA (LPC...
ICML
2006
IEEE
15 years 10 months ago
2006
IEEE
The problem of nonlinear dimensionality reduction is considered. We focus on problems where prior information is available, namely, semi-supervised dimensionality reduction. It is...
105
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PAMI
2007
14 years 9 months ago
2007
This paper considers the problem of dimensionality reduction by orthogonal projection techniques. The main feature of the proposed techniques is that they attempt to preserve both...