137 search results - page 7 / 28 » Ordinal Embedding: Approximation Algorithms and Dimensionali... |
IDA
1998
Springer
13 years 7 months ago
1998
Springer
A fast and simple algorithm for approximately calculating the principal components (PCs) of a data set and so reducing its dimensionality is described. This Simple Principal Compo...
ICPR
2008
IEEE
14 years 9 months ago
2008
IEEE
In this paper, we propose a new nonlinear dimensionality reduction algorithm by adopting regularized least-square criterion on local areas of the data distribution. We first propo...
ICML
2006
IEEE
14 years 8 months ago
2006
IEEE
We present a unified duality view of several recently emerged spectral methods for nonlinear dimensionality reduction, including Isomap, locally linear embedding, Laplacian eigenm...
WIRN
2005
Springer
14 years 1 months ago
2005
Springer
We present an algorithmic scheme for unsupervised cluster ensembles, based on randomized projections between metric spaces, by which a substantial dimensionality reduction is obtai...
ICML
2010
IEEE
13 years 8 months ago
2010
IEEE
Dimensionality reduction is a commonly used step in many algorithms for visualization, classification, clustering and modeling. Most dimensionality reduction algorithms find a low...