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BMCBI
2010
190views more  BMCBI 2010»
13 years 7 months ago
Sample size and statistical power considerations in high-dimensionality data settings: a comparative study of classification alg
Background: Data generated using `omics' technologies are characterized by high dimensionality, where the number of features measured per subject vastly exceeds the number of...
Yu Guo, Armin Graber, Robert N. McBurney, Raji Bal...
MM
2005
ACM
172views Multimedia» more  MM 2005»
14 years 1 months ago
Learning the semantics of multimedia queries and concepts from a small number of examples
In this paper we unify two supposedly distinct tasks in multimedia retrieval. One task involves answering queries with a few examples. The other involves learning models for seman...
Apostol Natsev, Milind R. Naphade, Jelena Tesic
BMCBI
2008
109views more  BMCBI 2008»
13 years 7 months ago
MetaFIND: A feature analysis tool for metabolomics data
Background: Metabolomics, or metabonomics, refers to the quantitative analysis of all metabolites present within a biological sample and is generally carried out using NMR spectro...
Kenneth Bryan, Lorraine Brennan, Padraig Cunningha...
SAC
2006
ACM
14 years 1 months ago
The impact of sample reduction on PCA-based feature extraction for supervised learning
“The curse of dimensionality” is pertinent to many learning algorithms, and it denotes the drastic raise of computational complexity and classification error in high dimension...
Mykola Pechenizkiy, Seppo Puuronen, Alexey Tsymbal
WWW
2006
ACM
14 years 8 months ago
Communities from seed sets
Expanding a seed set into a larger community is a common procedure in link-based analysis. We show how to adapt recent results from theoretical computer science to expand a seed s...
Reid Andersen, Kevin J. Lang