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CVPR
2008
IEEE
13 years 10 months ago
Improving local learning for object categorization by exploring the effects of ranking
Local learning for classification is useful in dealing with various vision problems. One key factor for such approaches to be effective is to find good neighbors for the learning ...
Tien-Lung Chang, Tyng-Luh Liu, Jen-Hui Chuang
BMCBI
2007
106views more  BMCBI 2007»
13 years 8 months ago
Improved classification accuracy in 1- and 2-dimensional NMR metabolomics data using the variance stabilising generalised logari
Background: Classifying nuclear magnetic resonance (NMR) spectra is a crucial step in many metabolomics experiments. Since several multivariate classification techniques depend up...
Helen M. Parsons, Christian Ludwig, Ulrich L. G&uu...
CSB
2003
IEEE
110views Bioinformatics» more  CSB 2003»
14 years 1 months ago
Prokaryote Phylogeny without Sequence Alignment: From Avoidance Signature to Composition Distance
A new and essentially simple method to reconstruct prokaryotic phylogenetic trees from their complete genome data without using sequence alignment is proposed. It is based on the ...
Bailin Hao, Ji Qi
ICMLA
2010
13 years 6 months ago
A New Approach to Classification with the Least Number of Features
Recently, the so-called Support Feature Machine (SFM) was proposed as a novel approach to feature selection for classification, based on minimisation of the zero norm of a separati...
Sascha Klement, Thomas Martinetz
CSDA
2011
13 years 3 months ago
Functional density synchronization
Estimating an overall density function from repeated observations on each of a sample of independent subjects or experimental units is of interest. An example is provided by biodem...
Zhen Zhang, Hans-Georg Müller