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ICASSP
2010
IEEE
13 years 7 months ago
A supervisory approach to semi-supervised clustering
We propose a new approach to semi-supervised clustering that utilizes boosting to simultaneously learn both a similarity measure and a clustering of the data from given instancele...
Bryan Conroy, Yongxin Taylor Xi, Peter J. Ramadge
KES
2004
Springer
14 years 3 months ago
Multi-modal Data Fusion: A Description
Clustering groups records that are similar to each other into the same group, and those that are less similar into different groups. Clustering data of mixed types is difficult du...
Sarah Coppock, Lawrence J. Mazlack
ICDAR
2003
IEEE
14 years 3 months ago
Optimizing Binary Feature Vector Similarity Measure using Genetic Algorithm and Handwritten Character Recognition
Classifying an unknown input is a fundamental problem in pattern recognition. A common method is to define a distance metric between patterns and find the most similar pattern i...
Sung-Hyuk Cha, Charles C. Tappert, Sargur N. Sriha...
BMCBI
2008
166views more  BMCBI 2008»
13 years 10 months ago
Biclustering via optimal re-ordering of data matrices in systems biology: rigorous methods and comparative studies
Background: The analysis of large-scale data sets via clustering techniques is utilized in a number of applications. Biclustering in particular has emerged as an important problem...
Peter A. DiMaggio Jr., Scott R. McAllister, Christ...
CCS
2009
ACM
14 years 10 months ago
The union-split algorithm and cluster-based anonymization of social networks
Knowledge discovery on social network data can uncover latent social trends and produce valuable findings that benefit the welfare of the general public. A growing amount of resea...
Brian Thompson, Danfeng Yao