Sciweavers

1051 search results - page 53 / 211
» An algorithm for the principal component analysis of large d...
Sort
View
GECCO
2006
Springer
186views Optimization» more  GECCO 2006»
13 years 11 months ago
Characterizing large text corpora using a maximum variation sampling genetic algorithm
An enormous amount of information available via the Internet exists. Much of this data is in the form of text-based documents. These documents cover a variety of topics that are v...
Robert M. Patton, Thomas E. Potok
DOCENG
2007
ACM
14 years 12 hour ago
Extracting reusable document components for variable data printing
Variable Data Printing (VDP) has brought new flexibility and dynamism to the printed page. Each printed instance of a specific class of document can now have different degrees of ...
Steven R. Bagley, David F. Brailsford, James A. Ol...
BMCBI
2011
12 years 11 months ago
To aggregate or not to aggregate high-dimensional classifiers
Background: High-throughput functional genomics technologies generate large amount of data with hundreds or thousands of measurements per sample. The number of sample is usually m...
Cheng-Jian Xu, Huub C. J. Hoefsloot, Age K. Smilde
CSDA
2006
83views more  CSDA 2006»
13 years 8 months ago
Linear grouping using orthogonal regression
A new method to detect different linear structures in a data set, called Linear Grouping Algorithm (LGA), is proposed. LGA is useful for investigating potential linear patterns in...
Stefan Van Aelst, Xiaogang Wang, Ruben H. Zamar, R...
NIPS
2003
13 years 9 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