177 search results - page 3 / 36 » K-means clustering via principal component analysis |
CORR
2007
Springer
14 years 9 months ago
2007
Springer
In this paper, we study the application of sparse principal component analysis (PCA) to clustering and feature selection problems. Sparse PCA seeks sparse factors, or linear combi...
101
Voted
WEBI
2001
Springer
15 years 1 months ago
2001
Springer
: Automated collaborative filtering is a popular technique for reducing information overload. In this paper, we propose a new approach for the collaborative filtering using local...
ECML
2004
Springer
15 years 2 months ago
2004
Springer
This work presents a novel procedure for computing (1) distances between nodes of a weighted, undirected, graph, called the Euclidean Commute Time Distance (ECTD), and (2) a subspa...
ICMLC
2010
Springer
14 years 8 months ago
2010
Springer
ICML
2009
IEEE
15 years 10 months ago
2009
IEEE
Clustering data in high dimensions is believed to be a hard problem in general. A number of efficient clustering algorithms developed in recent years address this problem by proje...