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WSC
2007
15 years 6 months ago
Kernel estimation for quantile sensitivities
Quantiles, also known as value-at-risk in financial applications, are important measures of random performance. Quantile sensitivities provide information on how changes in the i...
Guangwu Liu, L. Jeff Hong
ADMA
2005
Springer
134views Data Mining» more  ADMA 2005»
15 years 6 months ago
An LZ78 Based String Kernel
We develop the notion of normalized information distance (NID) [7] into a kernel distance suitable for use with a Support Vector Machine classifier, and demonstrate its use for an...
Ming Li, Ronan Sleep
BMCBI
2010
138views more  BMCBI 2010»
15 years 4 months ago
Amino acid classification based spectrum kernel fusion for protein subnuclear localization
Background: Prediction of protein localization in subnuclear organelles is more challenging than general protein subcelluar localization. There are only three computational models...
Suyu Mei, Wang Fei
PKDD
2010
Springer
179views Data Mining» more  PKDD 2010»
15 years 2 months ago
Laplacian Spectrum Learning
Abstract. The eigenspectrum of a graph Laplacian encodes smoothness information over the graph. A natural approach to learning involves transforming the spectrum of a graph Laplaci...
Pannagadatta K. Shivaswamy, Tony Jebara
ICIP
2008
IEEE
15 years 10 months ago
Raising in watershed lattices
The watershed segmentation is a popular tool in image processing. Starting from an initial map, the border thinning transformation produces a map whose minima constitute the catch...
Jean Cousty, Laurent Najman, Jean Serra