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DILS
2008
Springer
15 years 8 months ago
Semi Supervised Spectral Clustering for Regulatory Module Discovery
We propose a novel semi-supervised clustering method for the task of gene regulatory module discovery. The technique uses data on dna binding as prior knowledge to guide the proces...
Alok Mishra, Duncan Gillies
SDM
2007
SIAM
137views Data Mining» more  SDM 2007»
15 years 7 months ago
Are approximation algorithms for consensus clustering worthwhile?
Consensus clustering has emerged as one of the principal clustering problems in the data mining community. In recent years the theoretical computer science community has generated...
Michael Bertolacci, Anthony Wirth
PR
2007
107views more  PR 2007»
15 years 5 months ago
Newtonian clustering: An approach based on molecular dynamics and global optimization
Given a data set, a dynamical procedure is applied to the data points in order to shrink and separate, possibly overlapping clusters. Namely, Newton’s equations of motion are em...
Konstantinos Blekas, Isaac E. Lagaris
ICDM
2009
IEEE
117views Data Mining» more  ICDM 2009»
16 years 29 days ago
Redistricting Using Heuristic-Based Polygonal Clustering
— Redistricting is the process of dividing a geographic area into districts or zones. This process has been considered in the past as a problem that is computationally too comple...
Deepti Joshi, Leen-Kiat Soh, Ashok Samal
NIPS
2004
15 years 7 months ago
Maximum Margin Clustering
We propose a new method for clustering based on finding maximum margin hyperplanes through data. By reformulating the problem in terms of the implied equivalence relation matrix, ...
Linli Xu, James Neufeld, Bryce Larson, Dale Schuur...