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ICDM
2008
IEEE
122views Data Mining» more  ICDM 2008»
14 years 2 months ago
Nonnegative Matrix Factorization for Combinatorial Optimization: Spectral Clustering, Graph Matching, and Clique Finding
Nonnegative matrix factorization (NMF) is a versatile model for data clustering. In this paper, we propose several NMF inspired algorithms to solve different data mining problems....
Chris H. Q. Ding, Tao Li, Michael I. Jordan
PAKDD
2004
ACM
96views Data Mining» more  PAKDD 2004»
14 years 1 months ago
Spectral Energy Minimization for Semi-supervised Learning
The use of unlabeled data to aid classification is important as labeled data is often available in limited quantity. Instead of utilizing training samples directly into semi-super...
Chun Hung Li, Zhi-Li Wu
ICASSP
2010
IEEE
13 years 8 months ago
Evolutionary spectral clustering with adaptive forgetting factor
Many practical applications of clustering involve data collected over time. In these applications, evolutionary clustering can be applied to the data to track changes in clusters ...
Kevin S. Xu, Mark Kliger, Alfred O. Hero III
DATESO
2010
148views Database» more  DATESO 2010»
13 years 5 months ago
Using Spectral Clustering for Finding Students' Patterns of Behavior in Social Networks
Abstract. The high dimensionality of the data generated by social networks has been a big challenge for researchers. In order to solve the problems associated with this phenomenon,...
Gamila Obadi, Pavla Drázdilová, Jan ...
FOCS
2000
IEEE
14 years 7 days ago
On Clusterings - Good, Bad and Spectral
We motivate and develop a natural bicriteria measure for assessing the quality of a clustering that avoids the drawbacks of existing measures. A simple recursive heuristic is shown...
Ravi Kannan, Santosh Vempala, Adrian Vetta