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WILF
2007
Springer
147views Fuzzy Logic» more  WILF 2007»
13 years 11 months ago
Fuzzy Ensemble Clustering for DNA Microarray Data Analysis
Two major problems related the unsupervised analysis of gene expression data are represented by the accuracy and reliability of the discovered clusters, and by the biological fact ...
Roberto Avogadri, Giorgio Valentini
ICAI
2004
13 years 6 months ago
A Comparison of Resampling Methods for Clustering Ensembles
-- Combination of multiple clusterings is an important task in the area of unsupervised learning. Inspired by the success of supervised bagging algorithms, we propose a resampling ...
Behrouz Minaei-Bidgoli, Alexander P. Topchy, Willi...
SDM
2004
SIAM
218views Data Mining» more  SDM 2004»
13 years 6 months ago
Mixture Density Mercer Kernels: A Method to Learn Kernels Directly from Data
This paper presents a method of generating Mercer Kernels from an ensemble of probabilistic mixture models, where each mixture model is generated from a Bayesian mixture density e...
Ashok N. Srivastava
CRV
2009
IEEE
237views Robotics» more  CRV 2009»
13 years 11 months ago
SEC: Stochastic Ensemble Consensus Approach to Unsupervised SAR Sea-Ice Segmentation
The use of synthetic aperture radar (SAR) has become an integral part of sea-ice monitoring and analysis in the polar regions. An important task in sea-ice analysis is to segment ...
Alexander Wong, David A. Clausi, Paul W. Fieguth
ICCV
2009
IEEE
13 years 2 months ago
Simultaneous alignment and clustering for an image ensemble
Joint alignment for an image ensemble can rectify images in the spatial domain such that the aligned images are as similar to each other as possible. This important technology has...
Xiaoming Liu 0002, Yan Tong, Frederick W. Wheeler