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LATIN
2010
Springer
15 years 4 months ago
Kernelization through Tidying
Abstract. We introduce the NP-hard graph-based data clustering problem s-Plex Cluster Vertex Deletion, where the task is to delete at most k vertices from a graph so that the conne...
René van Bevern, Hannes Moser, Rolf Niederm...
SDM
2010
SIAM
213views Data Mining» more  SDM 2010»
14 years 11 months ago
Spectral Analysis of Signed Graphs for Clustering, Prediction and Visualization
We study the application of spectral clustering, prediction and visualization methods to graphs with negatively weighted edges. We show that several characteristic matrices of gra...
Jérôme Kunegis, Stephan Schmidt, Andr...
IJCAI
2003
14 years 11 months ago
Continuous nonlinear dimensionality reduction by kernel Eigenmaps
We equate nonlinear dimensionality reduction (NLDR) to graph embedding with side information about the vertices, and derive a solution to either problem in the form of a kernel-ba...
Matthew Brand
PR
2008
169views more  PR 2008»
14 years 9 months ago
A survey of kernel and spectral methods for clustering
Clustering algorithms are a useful tool to explore data structures and have been employed in many disciplines. The focus of this paper is the partitioning clustering problem with ...
Maurizio Filippone, Francesco Camastra, Francesco ...
PAKDD
2011
ACM
253views Data Mining» more  PAKDD 2011»
14 years 20 days ago
Balance Support Vector Machines Locally Using the Structural Similarity Kernel
A structural similarity kernel is presented in this paper for SVM learning, especially for learning with imbalanced datasets. Kernels in SVM are usually pairwise, comparing the sim...
Jianxin Wu