30 search results - page 4 / 6 » ISOLLE: Locally Linear Embedding with Geodesic Distance |
ECCV
2004
Springer
15 years 11 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...
KDD
2006
ACM
15 years 9 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...
PKDD
2010
Springer
14 years 7 months ago
2010
Springer
The foremost nonlinear dimensionality reduction algorithms provide an embedding only for the given training data, with no straightforward extension for test points. This shortcomin...
ICML
2005
IEEE
15 years 10 months ago
2005
IEEE
Many unsupervised algorithms for nonlinear dimensionality reduction, such as locally linear embedding (LLE) and Laplacian eigenmaps, are derived from the spectral decompositions o...
SIAMJO
2010
14 years 4 months ago
2010
The sensor network localization, SNL , problem in embedding dimension r, consists of locating the positions of wireless sensors, given only the distances between sensors that are ...