602 search results - page 2 / 121 » A Least-Squares Framework for Component Analysis |
CVPR
2007
IEEE
14 years 6 months ago
2007
IEEE
Linear Discriminant Analysis (LDA) is a popular statistical approach for dimensionality reduction. LDA captures the global geometric structure of the data by simultaneously maximi...
ISNN
2007
Springer
13 years 10 months ago
2007
Springer
Nonnegative Matrix and Tensor Factorization (NMF/NTF) and Sparse Component Analysis (SCA) have already found many potential applications, especially in multi-way Blind Source Separ...
CJ
1998
13 years 4 months ago
1998
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...
SMI
2006
IEEE
13 years 10 months ago
2006
IEEE
In this paper, we propose a constrained least squares approach for stably computing Laplacian deformation with strict positional constraints. In the existing work on Laplacian def...
TSP
2008
13 years 4 months ago
2008
Since the seminal work of Stein in the 1950s, there has been continuing research devoted to improving the total meansquared error (MSE) of the least-squares (LS) estimator in the l...