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ICML
2007
IEEE
16 years 5 months ago
Least squares linear discriminant analysis
Linear Discriminant Analysis (LDA) is a well-known method for dimensionality reduction and classification. LDA in the binaryclass case has been shown to be equivalent to linear re...
Jieping Ye
ICML
2007
IEEE
16 years 5 months ago
Full regularization path for sparse principal component analysis
Given a sample covariance matrix, we examine the problem of maximizing the variance explained by a particular linear combination of the input variables while constraining the numb...
Alexandre d'Aspremont, Francis R. Bach, Laurent El...
ICML
2008
IEEE
16 years 5 months ago
Robust matching and recognition using context-dependent kernels
The success of kernel methods including support vector machines (SVMs) strongly depends on the design of appropriate kernels. While initially kernels were designed in order to han...
Hichem Sahbi, Jean-Yves Audibert, Jaonary Rabariso...
ICML
2008
IEEE
16 years 5 months ago
A least squares formulation for canonical correlation analysis
Canonical Correlation Analysis (CCA) is a well-known technique for finding the correlations between two sets of multi-dimensional variables. It projects both sets of variables int...
Liang Sun, Shuiwang Ji, Jieping Ye
ICML
2006
IEEE
16 years 5 months ago
Learning hierarchical task networks by observation
Knowledge-based planning methods offer benefits over classical techniques, but they are time consuming and costly to construct. There has been research on learning plan knowledge ...
Negin Nejati, Pat Langley, Tolga Könik