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» Hierarchical Unsupervised Learning
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166
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AAAI
2010
15 years 6 months ago
Efficient Spectral Feature Selection with Minimum Redundancy
Spectral feature selection identifies relevant features by measuring their capability of preserving sample similarity. It provides a powerful framework for both supervised and uns...
Zheng Zhao, Lei Wang, Huan Liu
ICONIP
2007
15 years 6 months ago
Using Image Stimuli to Drive fMRI Analysis
We introduce a new unsupervised fMRI analysis method based on Kernel Canonical Correlation Analysis which differs from the class of supervised learning methods that are increasing...
David R. Hardoon, Janaina Mourão Miranda, M...
ICAI
2004
15 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...
DATAMINE
2006
157views more  DATAMINE 2006»
15 years 5 months ago
Data Clustering with Partial Supervision
Clustering with partial supervision finds its application in situations where data is neither entirely nor accurately labeled. This paper discusses a semisupervised clustering algo...
Abdelhamid Bouchachia, Witold Pedrycz
171
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JMLR
2010
110views more  JMLR 2010»
15 years 3 months ago
Information Retrieval Perspective to Nonlinear Dimensionality Reduction for Data Visualization
Nonlinear dimensionality reduction methods are often used to visualize high-dimensional data, although the existing methods have been designed for other related tasks such as mani...
Jarkko Venna, Jaakko Peltonen, Kristian Nybo, Hele...