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We present a unified duality view of several recently emerged spectral methods for nonlinear dimensionality reduction, including Isomap, locally linear embedding, Laplacian eigenmaps, and maximum vari...
Fat quality is determined by the composition of fatty acids. Genetic relationships between this composition and single nucleotide polymorphisms (SNPs) in the stearoyl-CoA desaturase1 (SCD1) gene were ...
Linear methods of dimensionality reduction are useful tools for handling and interpreting high dimensional data. However, the cumulative variance explained by each of the subspaces in which the data s...
Linear dimensionality reduction techniques, notably principal component analysis, are widely used in climate data analysis as a means to aid in the interpretation of datasets of high dimensionality. T...
Studies to detect genes responsible for economic traits in farm animals have been performed using parametric linear models. A non-parametric, model-free approach using the ??expanded multifactor-dimen...

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