154 search results - page 5 / 31 » Incremental Nonlinear Dimensionality Reduction by Manifold L... |
92
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AAAI
2007
15 years 1 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...
119
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ICML
2007
IEEE
16 years 12 days ago
2007
IEEE
In this work we take a novel view of nonlinear manifold learning. Usually, manifold learning is formulated in terms of finding an embedding or `unrolling' of a manifold into ...
ICCV
2007
IEEE
15 years 6 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...
ACAL
2007
Springer
15 years 1 months ago
2007
Springer
This paper addresses the topic of how architectural visual experience can be represented and utilised by a software system. The long-term aim is to equip an artificial agent with ...
CVPR
2008
IEEE
16 years 1 months ago
2008
IEEE
Linear Discriminant Analysis (LDA), which works by maximizing the within-class similarity and minimizing the between-class similarity simultaneously, is a popular dimensionality r...