141 search results - page 23 / 29 » Grouping and dimensionality reduction by locally linear embe... |
NIPS
2007
13 years 9 months ago
2007
Maximum variance unfolding (MVU) is an effective heuristic for dimensionality reduction. It produces a low-dimensional representation of the data by maximizing the variance of the...
CVPR
2003
IEEE
14 years 9 months ago
2003
IEEE
By mapping a set of input images to points in a lowdimensional manifold or subspace, it is possible to efficiently account for a small number of degrees of freedom. For example, i...
KDD
2006
ACM
14 years 8 months ago
2006
ACM
Calculation of object similarity, for example through a distance function, is a common part of data mining and machine learning algorithms. This calculation is crucial for efficie...
CVPR
2007
IEEE
14 years 9 months ago
2007
IEEE
Linear and affine subspaces are commonly used to describe appearance of objects under different lighting, viewpoint, articulation, and identity. A natural problem arising from the...
CVPR
2008
IEEE
14 years 9 months ago
2008
IEEE
In this paper, an analysis of locally linear embedding (LLE) in the context of clustering is developed. As LLE conserves the local affine coordinates of points, shape protrusions ...