148 search results - page 6 / 30 » Riemannian Manifold Learning for Nonlinear Dimensionality Re... |
ICML
2007
IEEE
14 years 8 months 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
14 years 1 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
13 years 9 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
14 years 9 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...
ICASSP
2007
IEEE
14 years 1 months ago
2007
IEEE
A novel method for robust super-resolution offace images is proposed in this paper. Face super-resolution is a particular interest in video surveillance where face images have typ...