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NIPS
2004
13 years 8 months ago
Proximity Graphs for Clustering and Manifold Learning
Many machine learning algorithms for clustering or dimensionality reduction take as input a cloud of points in Euclidean space, and construct a graph with the input data points as...
Miguel Á. Carreira-Perpiñán, ...
CVPR
2005
IEEE
14 years 9 months ago
Subspace Analysis Using Random Mixture Models
In [1], three popular subspace face recognition methods, PCA, Bayes, and LDA were analyzed under the same framework and an unified subspace analysis was proposed. However, since t...
Xiaogang Wang, Xiaoou Tang
CVPR
2003
IEEE
14 years 9 months ago
Joint Manifold Distance: a new approach to appearance based clustering
We wish to match sets of images to sets of images where both sets are undergoing various distortions such as viewpoint and lighting changes. To this end we have developed a Joint ...
Andrew W. Fitzgibbon, Andrew Zisserman
NIPS
2008
13 years 8 months ago
Convergence and Rate of Convergence of a Manifold-Based Dimension Reduction Algorithm
We study the convergence and the rate of convergence of a local manifold learning algorithm: LTSA [13]. The main technical tool is the perturbation analysis on the linear invarian...
Andrew Smith, Xiaoming Huo, Hongyuan Zha
ICDM
2006
IEEE
110views Data Mining» more  ICDM 2006»
14 years 1 months ago
Manifold Clustering of Shapes
Shape clustering can significantly facilitate the automatic labeling of objects present in image collections. For example, it could outline the existing groups of pathological ce...
Dragomir Yankov, Eamonn J. Keogh