26 search results - page 3 / 6 » Flexible constrained spectral clustering |
KDD
2009
ACM
14 years 5 months ago
2009
ACM
The aim of data mining is to find novel and actionable insights in data. However, most algorithms typically just find a single (possibly non-novel/actionable) interpretation of th...
KDD
2009
ACM
14 years 5 months ago
2009
ACM
Spectral clustering refers to a flexible class of clustering procedures that can produce high-quality clusterings on small data sets but which has limited applicability to large-s...
BMCBI
2005
13 years 5 months ago
2005
Background: Graph theory provides a computational framework for modeling a variety of datasets including those emerging from genomics, proteomics, and chemical genetics. Networks ...
CORR
2010
Springer
13 years 2 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...
TKDE
2012
11 years 7 months ago
2012
—The pairwise constraints specifying whether a pair of samples should be grouped together or not have been successfully incorporated into the conventional clustering methods such...