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» Supervised dimensionality reduction using mixture models
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TMI
2008
136views more  TMI 2008»
15 years 3 months ago
Classification of fMRI Time Series in a Low-Dimensional Subspace With a Spatial Prior
We propose a new method for detecting activation in functional magnetic resonance imaging (fMRI) data. We project the fMRI time series on a low-dimensional subspace spanned by wave...
François G. Meyer, Xilin Shen
123
Voted
ACMACE
2008
ACM
15 years 5 months ago
Dimensionality reduced HRTFs: a comparative study
Dimensionality reduction is a statistical tool commonly used to map high-dimensional data into lower a dimensionality. The transformed data is typically more suitable for regressi...
Bill Kapralos, Nathan Mekuz, Agnieszka Kopinska, S...
ICCS
2007
Springer
15 years 9 months ago
Hessian-Based Model Reduction for Large-Scale Data Assimilation Problems
Assimilation of spatially- and temporally-distributed state observations into simulations of dynamical systems stemming from discretized PDEs leads to inverse problems with high-di...
Omar Bashir, Omar Ghattas, Judith Hill, Bart G. va...
BMCBI
2007
128views more  BMCBI 2007»
15 years 3 months ago
Combining classifiers to predict gene function in Arabidopsis thaliana using large-scale gene expression measurements
Background: Arabidopsis thaliana is the model species of current plant genomic research with a genome size of 125 Mb and approximately 28,000 genes. The function of half of these ...
Hui Lan, Rachel Carson, Nicholas J. Provart, Antho...
175
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TSMC
2010
14 years 10 months ago
Distance Approximating Dimension Reduction of Riemannian Manifolds
We study the problem of projecting high-dimensional tensor data on an unspecified Riemannian manifold onto some lower dimensional subspace1 without much distorting the pairwise geo...
Changyou Chen, Junping Zhang, Rudolf Fleischer