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SODA
2010
ACM
189views Algorithms» more  SODA 2010»
14 years 7 months ago
Correlation Clustering with Noisy Input
Correlation clustering is a type of clustering that uses a basic form of input data: For every pair of data items, the input specifies whether they are similar (belonging to the s...
Claire Mathieu, Warren Schudy
ICML
2005
IEEE
14 years 10 months ago
Semi-supervised graph clustering: a kernel approach
Semi-supervised clustering algorithms aim to improve clustering results using limited supervision. The supervision is generally given as pairwise constraints; such constraints are...
Brian Kulis, Sugato Basu, Inderjit S. Dhillon, Ray...
WACV
2005
IEEE
14 years 3 months ago
Ensemble Methods in the Clustering of String Patterns
We address the problem of clustering of contour images from hardware tools based on string descriptions, in a comparative study of cluster combination techniques. Several clusteri...
André Lourenço, Ana L. N. Fred
MOC
2000
96views more  MOC 2000»
13 years 9 months ago
Galerkin eigenvector approximations
How close are Galerkin eigenvectors to the best approximation available out of the trial subspace? Under a variety of conditions the Galerkin method gives an approximate eigenvecto...
Christopher Beattie
SDM
2010
SIAM
153views Data Mining» more  SDM 2010»
13 years 11 months ago
Reconstruction from Randomized Graph via Low Rank Approximation
The privacy concerns associated with data analysis over social networks have spurred recent research on privacypreserving social network analysis, particularly on privacypreservin...
Leting Wu, Xiaowei Ying, Xintao Wu