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» Dimensionality Reduction of Clustered Data Sets
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JMLR
2010
119views more  JMLR 2010»
13 years 3 months ago
Hubs in Space: Popular Nearest Neighbors in High-Dimensional Data
Different aspects of the curse of dimensionality are known to present serious challenges to various machine-learning methods and tasks. This paper explores a new aspect of the dim...
Milos Radovanovic, Alexandros Nanopoulos, Mirjana ...
ISCA
2007
IEEE
217views Hardware» more  ISCA 2007»
13 years 8 months ago
Parallel Processing of High-Dimensional Remote Sensing Images Using Cluster Computer Architectures
Hyperspectral sensors represent the most advanced instruments currently available for remote sensing of the Earth. The high spatial and spectral resolution of the images supplied ...
David Valencia, Antonio Plaza, Pablo Martín...
ICDM
2009
IEEE
176views Data Mining» more  ICDM 2009»
13 years 6 months ago
SISC: A Text Classification Approach Using Semi Supervised Subspace Clustering
Text classification poses some specific challenges. One such challenge is its high dimensionality where each document (data point) contains only a small subset of them. In this pap...
Mohammad Salim Ahmed, Latifur Khan
JMLR
2010
115views more  JMLR 2010»
13 years 3 months ago
O-IPCAC and its Application to EEG Classification
In this paper we describe an online/incremental linear binary classifier based on an interesting approach to estimate the Fisher subspace. The proposed method allows to deal with ...
Alessandro Rozza, Gabriele Lombardi, Marco Rosa, E...
RSFDGRC
2005
Springer
100views Data Mining» more  RSFDGRC 2005»
14 years 2 months ago
A Hybrid Approach to MR Imaging Segmentation Using Unsupervised Clustering and Approximate Reducts
Abstract. We introduce a hybrid approach to magnetic resonance image segmentation using unsupervised clustering and the rules derived from approximate decision reducts. We utilize ...
Sebastian Widz, Kenneth Revett, Dominik Slezak