879 search results - page 100 / 176 » Forecasting high-dimensional data |
157
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PAMI
1998
15 years 5 months ago
1998
A new method for analyzing the intrinsic dimensionality (ID) of low dimensional manifolds in high dimensional feature spaces is presented. The basic idea is to rst extract a low-d...
168
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CVPR
2008
IEEE
16 years 8 months ago
2008
IEEE
Given a finite number of data points sampled from a low-dimensional manifold embedded in a high dimensional space together with the parameter vectors for a subset of the data poin...
194
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ECML
2007
Springer
16 years 10 days ago
2007
Springer
Abstract. Principal component analysis (PCA) is a well-known classical data analysis technique. There are a number of algorithms for solving the problem, some scaling better than o...
186
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AAAI
2007
15 years 8 months ago
2007
Recently the problem of dimensionality reduction has received a lot of interests in many fields of information processing. We consider the case where data is sampled from a low d...
169
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PKDD
2010
Springer
15 years 4 months ago
2010
Springer
Abstract. Semi-supervised clustering models, that incorporate user provided constraints to yield meaningful clusters, have recently become a popular area of research. In this paper...