325 search results - page 20 / 65 » On Clusterings - Good, Bad and Spectral |
CORR
2010
Springer
13 years 5 months ago
2010
Springer
Many problems in machine learning and statistics can be formulated as (generalized) eigenproblems. In terms of the associated optimization problem, computing linear eigenvectors a...
ICML
2010
IEEE
13 years 9 months ago
2010
IEEE
We describe an algorithm for clustering using a similarity graph. The algorithm (a) runs in O(n log3 n + m log n) time on graphs with n vertices and m edges, and (b) with high pro...
JCP
2007
13 years 8 months ago
2007
Abstract— Analyzing unknown data sets such as multispectral images often requires unsupervised techniques. Data clustering is a well known and widely used approach in such cases....
NIPS
2001
13 years 9 months ago
2001
The popular K-means clustering partitions a data set by minimizing a sum-of-squares cost function. A coordinate descend method is then used to nd local minima. In this paper we sh...
ICASSP
2009
IEEE
14 years 3 months ago
2009
IEEE
In this paper we investigate the use of data driven clustering methods for functional connectivity analysis in fMRI. In particular, we consider the K-Means and Spectral Clustering...