Sciweavers

161 search results - page 8 / 33
» Least Squares SVM for Least Squares TD Learning
Sort
View
CJ
1998
118views more  CJ 1998»
14 years 9 months ago
Least-Squares Structuring, Clustering and Data Processing Issues
Approximation structuring clustering is an extension of what is usually called square-error clustering" onto various cluster structures and data formats. It appears to be not...
Boris Mirkin
JMLR
2010
145views more  JMLR 2010»
14 years 4 months ago
Kernel Partial Least Squares is Universally Consistent
We prove the statistical consistency of kernel Partial Least Squares Regression applied to a bounded regression learning problem on a reproducing kernel Hilbert space. Partial Lea...
Gilles Blanchard, Nicole Krämer
ICASSP
2011
IEEE
14 years 1 months ago
A partial least squares framework for speaker recognition
Modern approaches to speaker recognition (verification) operate in a space of “supervectors” created via concatenation of the mean vectors of a Gaussian mixture model (GMM) a...
Balaji Vasan Srinivasan, Dmitry N. Zotkin, Ramani ...
ICDM
2009
IEEE
120views Data Mining» more  ICDM 2009»
15 years 4 months ago
Least Square Incremental Linear Discriminant Analysis
Abstract—Linear discriminant analysis (LDA) is a wellknown dimension reduction approach, which projects highdimensional data into a low-dimensional space with the best separation...
Li-Ping Liu, Yuan Jiang, Zhi-Hua Zhou
FLAIRS
2004
14 years 10 months ago
Gene Expression Data Classification with Revised Kernel Partial Least Squares Algorithm
One important feature of the gene expression data is that the number of genes M far exceeds the number of samples N. Standard statistical methods do not work well when N < M. D...
ZhenQiu Liu, Dechang Chen