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» Dimensionality Reduction of Clustered Data Sets
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SIGMOD
2002
ACM
246views Database» more  SIGMOD 2002»
14 years 8 months ago
Hierarchical subspace sampling: a unified framework for high dimensional data reduction, selectivity estimation and nearest neig
With the increased abilities for automated data collection made possible by modern technology, the typical sizes of data collections have continued to grow in recent years. In suc...
Charu C. Aggarwal
CORR
2011
Springer
151views Education» more  CORR 2011»
13 years 3 months ago
A supervised clustering approach for fMRI-based inference of brain states
We propose a method that combines signals from many brain regions observed in functional Magnetic Resonance Imaging (fMRI) to predict the subject’s behavior during a scanning se...
Vincent Michel, Alexandre Gramfort, Gaël Varo...
SDM
2007
SIAM
108views Data Mining» more  SDM 2007»
13 years 10 months ago
Semi-Supervised Dimensionality Reduction
Dimensionality reduction is among the keys in mining highdimensional data. This paper studies semi-supervised dimensionality reduction. In this setting, besides abundant unlabeled...
Daoqiang Zhang, Zhi-Hua Zhou, Songcan Chen
SISAP
2008
IEEE
188views Data Mining» more  SISAP 2008»
14 years 2 months ago
High-Dimensional Similarity Retrieval Using Dimensional Choice
There are several pieces of information that can be utilized in order to improve the efficiency of similarity searches on high-dimensional data. The most commonly used information...
Dave Tahmoush, Hanan Samet
CSDA
2007
58views more  CSDA 2007»
13 years 8 months ago
A unifying model involving a categorical and/or dimensional reduction for multimode data
A unifying model is presented that implies a categorical and/or dimensional reduction of one or several modes of a multiway data set. The model encompasses a broad range of (exist...
Iven Van Mechelen, Jan Schepers