791 search results - page 72 / 159 » Non-Linear Dimensionality Reduction |
168
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ECCV
2004
Springer
16 years 6 months ago
2004
Springer
Abstract. Dimensionality reduction is an essential aspect of visual processing. Traditionally, linear dimensionality reduction techniques such as principle components analysis have...
143
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ICML
2010
IEEE
15 years 5 months ago
2010
IEEE
Dimension reduction is popular for learning predictive models in high-dimensional spaces. It can highlight the relevant part of the feature space and avoid the curse of dimensiona...
178
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JMLR
2012
13 years 7 months ago
2012
Metric and kernel learning arise in several machine learning applications. However, most existing metric learning algorithms are limited to learning metrics over low-dimensional d...
131
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ICML
2008
IEEE
16 years 5 months ago
2008
IEEE
In this paper we introduce a novel approach to manifold alignment, based on Procrustes analysis. Our approach differs from "semisupervised alignment" in that it results ...
129
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KDD
2003
ACM
16 years 5 months ago
2003
ACM
Dimensionality reduction via Random Projections has attracted considerable attention in recent years. The approach has interesting theoretical underpinnings and offers computation...