33 search results - page 4 / 7 » Laplacian Eigenmaps and Spectral Techniques for Embedding an... |
ML
2010
ACM
13 years 17 days ago
2010
ACM
Spectral analysis approaches have been actively studied in machine learning and data mining areas, due to their generality, efficiency, and rich theoretical foundations. As a natur...
PAMI
2012
11 years 8 months ago
2012
— Over the last century, Component Analysis (CA) methods such as Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), Canonical Correlation Analysis (CCA), Lap...
JMLR
2011
13 years 22 days ago
2011
Following Hartigan (1975), a cluster is defined as a connected component of the t-level set of the underlying density, that is, the set of points for which the density is greater...
KDD
2010
ACM
13 years 9 months ago
2010
ACM
Constrained clustering has been well-studied for algorithms like K-means and hierarchical agglomerative clustering. However, how to encode constraints into spectral clustering rem...
CVPR
2008
IEEE
14 years 7 months ago
2008
IEEE
Matching articulated shapes represented by voxel-sets reduces to maximal sub-graph isomorphism when each set is described by a weighted graph. Spectral graph theory can be used to...