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» A Tutorial on Spectral Clustering
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WSC
2004
13 years 8 months ago
Stochastic Petri Nets for Modelling and Simulation
Stochastic Petri nets (SPNs) have proven to be a powerful and enduring graphically-oriented framework for modelling and performance analysis of complex systems. This tutorial focu...
Peter J. Haas
IGARSS
2009
13 years 5 months ago
Endmember Extraction from Hyperspectral Imagery using a Parallel Ensemble Approach with Consensus Analysis
We have explored in this paper a framework to test in a quantitative manner the stability of different endmember extraction and spectral unmixing algorithms based on the concept o...
Fermin Ayuso, Javier Setoain, Manuel Prieto, Chris...
SSPR
2004
Springer
14 years 22 days ago
Finding Clusters and Components by Unsupervised Learning
We present a tutorial survey on some recent approaches to unsupervised machine learning in the context of statistical pattern recognition. In statistical PR, there are two classica...
Erkki Oja
PAMI
2007
202views more  PAMI 2007»
13 years 6 months ago
Weighted Graph Cuts without Eigenvectors A Multilevel Approach
—A variety of clustering algorithms have recently been proposed to handle data that is not linearly separable; spectral clustering and kernel k-means are two of the main methods....
Inderjit S. Dhillon, Yuqiang Guan, Brian Kulis
PRL
2008
135views more  PRL 2008»
13 years 7 months ago
A hierarchical clustering algorithm based on the Hungarian method
We propose a novel hierarchical clustering algorithm for data-sets in which only pairwise distances between the points are provided. The classical Hungarian method is an efficient...
Jacob Goldberger, Tamir Tassa