165 search results - page 25 / 33 » Adaptive dimension reduction for clustering high dimensional... |
107
Voted
NIPS
1997
15 years 1 months ago
1997
I present an expectation-maximization (EM) algorithm for principal component analysis (PCA). The algorithm allows a few eigenvectors and eigenvalues to be extracted from large col...
115
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ICAPR
2001
Springer
15 years 4 months ago
2001
Springer
The goal of this paper is to describe an efficient procedure for color-based image retrieval. The proposed procedure consists of two stages. First, the image data set is hierarchi...
171
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ISNN
2011
Springer
14 years 2 months ago
2011
Springer
This paper presents a new method that uses orthogonalized features for time series clustering and classification. To cluster or classify time series data, either original data or...
101
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CVPR
2000
IEEE
15 years 3 months ago
2000
IEEE
Nearest neighbor classification assumes locally constant class conditional probabilities. This assumption becomes invalid in high dimensions with finite samples due to the curse o...
IJCAI
2007
15 years 1 months ago
2007
Kernel based nonlinear Feature Extraction (KFE) or dimensionality reduction is a widely used pre-processing step in pattern classification and data mining tasks. Given a positive...