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ICDE
2003
IEEE
193views Database» more  ICDE 2003»
14 years 7 months ago
An Adaptive and Efficient Dimensionality Reduction Algorithm for High-Dimensional Indexing
The notorious "dimensionality curse" is a well-known phenomenon for any multi-dimensional indexes attempting to scale up to high dimensions. One well known approach to o...
Hui Jin, Beng Chin Ooi, Heng Tao Shen, Cui Yu, Aoy...
BMCBI
2010
243views more  BMCBI 2010»
13 years 6 months ago
Comparative study of unsupervised dimension reduction techniques for the visualization of microarray gene expression data
Background: Visualization of DNA microarray data in two or three dimensional spaces is an important exploratory analysis step in order to detect quality issues or to generate new ...
Christoph Bartenhagen, Hans-Ulrich Klein, Christia...
VISSYM
2004
13 years 7 months ago
Volume Visualization and Visual Queries for Large High-Dimensional Datasets
We propose a flexible approach for the visualization of large, high-dimensional datasets. The raw, highdimensional data is mapped into an abstract 3D distance space using the Fast...
Guido Reina, Thomas Ertl
TVCG
2011
152views more  TVCG 2011»
13 years 1 months ago
Automated Analytical Methods to Support Visual Exploration of High-Dimensional Data
—Visual exploration of multivariate data typically requires projection onto lower-dimensional representations. The number of possible representations grows rapidly with the numbe...
Andrada Tatu, Georgia Albuquerque, Martin Eisemann...
TSP
2008
117views more  TSP 2008»
13 years 6 months ago
Sample Eigenvalue Based Detection of High-Dimensional Signals in White Noise Using Relatively Few Samples
The detection and estimation of signals in noisy, limited data is a problem of interest to many scientific and engineering communities. We present a mathematically justifiable, com...
R. R. Nadakuditi, A. Edelman