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» Intractability and clustering with constraints
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ICPR
2008
IEEE
15 years 11 months ago
K-means clustering of proportional data using L1 distance
We present a new L1-distance-based k-means clustering algorithm to address the challenge of clustering high-dimensional proportional vectors. The new algorithm explicitly incorpor...
Bonnie K. Ray, Hisashi Kashima, Jianying Hu, Monin...
IAT
2010
IEEE
14 years 7 months ago
An Interactive Tool for Constrained Clustering with Human Sampling
Abstract--This paper describes an interactive tool for constrained clustering that helps users to select effective constraints efficiently during the constrained clustering process...
Masayuki Okabe, Seiji Yamada
CORR
2007
Springer
130views Education» more  CORR 2007»
14 years 9 months ago
Lagrangian Relaxation for MAP Estimation in Graphical Models
Abstract— We develop a general framework for MAP estimation in discrete and Gaussian graphical models using Lagrangian relaxation techniques. The key idea is to reformulate an in...
Jason K. Johnson, Dmitry M. Malioutov, Alan S. Wil...
BMCBI
2010
115views more  BMCBI 2010»
14 years 9 months ago
Multiconstrained gene clustering based on generalized projections
Background: Gene clustering for annotating gene functions is one of the fundamental issues in bioinformatics. The best clustering solution is often regularized by multiple constra...
Jia Zeng, Shanfeng Zhu, Alan Wee-Chung Liew, Hong ...
VIP
2000
14 years 11 months ago
A System for Graph Clustering Based on User Hints
This paper presents a system for graph clustering where users can visualize the clustering and give "hints" that help a computing method to find better solutions. Hints ...
Hugo A. D. do Nascimento, Peter Eades