31 search results - page 6 / 7 » Kernel k-means: spectral clustering and normalized cuts |
TIP
2010
13 years 14 days ago
2010
In this paper, we propose a new image clustering algorithm, referred to as Clustering using Local Discriminant Models and Global Integration (LDMGI). To deal with the data points s...
ML
2010
ACM
13 years 16 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...
CVPR
2010
IEEE
14 years 2 months ago
2010
IEEE
Purely bottom-up, unsupervised segmentation of a single
image into two segments remains a challenging task for
computer vision. The co-segmentation problem is the process
of joi...
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...
ICDM
2010
IEEE
13 years 3 months ago
2010
IEEE
An idealized clustering algorithm seeks to learn a cluster-adjacency matrix such that, if two data points belong to the same cluster, the corresponding entry would be 1; otherwise ...