766 search results - page 73 / 154 » Clustering high dimensional data using subspace and projecte... |
EDBT
2004
ACM
14 years 9 months ago
2004
ACM
We present a novel anytime version of partitional clustering algorithm, such as k-Means and EM, for time series. The algorithm works by leveraging off the multi-resolution property...
PDPTA
2003
13 years 10 months ago
2003
Current systems for managing workload on clusters of workstations, particularly those available for Linux-based (Beowulf) clusters, are typically based on traditional process-base...
ICPR
2006
IEEE
14 years 10 months ago
2006
IEEE
Distance functions are an important component in many learning applications. However, the correct function is context dependent, therefore it is advantageous to learn a distance f...
IVC
2007
13 years 8 months ago
2007
- Canonical correlation analysis (CCA) is a major linear subspace approach to dimensionality reduction and has been applied to image processing, pose estimation and other fields. H...
CSDA
2007
13 years 8 months ago
2007
In this paper, we propose a novel non-parametric clustering method based on non-parametric local shrinking. Each data point is transformed in such a way that it moves a specific ...