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» Knowledge-based data analysis and interpretation
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NIPS
2003
14 years 11 months ago
Gaussian Process Latent Variable Models for Visualisation of High Dimensional Data
In this paper we introduce a new underlying probabilistic model for principal component analysis (PCA). Our formulation interprets PCA as a particular Gaussian process prior on a ...
Neil D. Lawrence
PRL
2006
98views more  PRL 2006»
14 years 9 months ago
Data complexity assessment in undersampled classification of high-dimensional biomedical data
Regularized linear classifiers have been successfully applied in undersampled, i.e. small sample size/high dimensionality biomedical classification problems. Additionally, a desig...
Richard Baumgartner, Ray L. Somorjai
ICASSP
2007
IEEE
15 years 4 months ago
Local Linear Discriminant Analysis (LLDA) for Inference of Multisubject FMRI Data
Large intersubject variability is a well-described feature of fMRI studies, making inter-group inference, of critical importance for biological interpretation, difficult. Therefor...
Martin J. McKeown, Junning Li, Xuemei Huang, Z. Ja...
BALT
2006
15 years 1 months ago
A Multiple Correspondence Analysis to Organize Data Cubes
Abstract. On Line Analytical Processing (OLAP) is a technology basically created to provide users with tools in order to explore and navigate into data cubes. Unfortunately, in hug...
Riadh Ben Messaoud, Omar Boussaid, Sabine Loudcher...
LWA
2008
14 years 11 months ago
Pre analysis and clustering of uncertain data from manufacturing processes
With increasing complexity of manufacturing processes, the volume of data that has to be evaluated rises accordingly. The complexity and data volume make any kind of manual data a...
Peter Benjamin Volk, Martin Hahmann, Dirk Habich, ...