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ICML
2007
IEEE
14 years 9 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
ICCV
2009
IEEE
15 years 1 months ago
Sparse Representation of Cast Shadows via L1-Regularized Least Squares
Scenes with cast shadows can produce complex sets of images. These images cannot be well approximated by lowdimensional linear subspaces. However, in this paper we show that the...
Xue Mei, Haibin Ling, David W. Jacobs
WSC
2008
13 years 11 months ago
Nonlinear process modeling and optimization based on Multiway Kernel Partial Least Squares model
MKPLS (Multiway Kernel Partial Least Squares) methods are used to model the batch processes from process operational data. To improve the optimization performance, a batch-to-batc...
Liqing Di, Zhihua Xiong, XianHui Yang
SIAMSC
2010
142views more  SIAMSC 2010»
13 years 7 months ago
Nested Iteration and First-Order System Least Squares for Incompressible, Resistive Magnetohydrodynamics
This paper develops a nested iteration algorithm to solve time-dependent nonlinear systems of partial differential equations. For each time step, Newton’s method is used to form...
J. H. Adler, Thomas A. Manteuffel, Stephen F. McCo...
SIAMSC
2011
142views more  SIAMSC 2011»
13 years 3 months ago
Efficiency Based Adaptive Local Refinement for First-Order System Least-Squares Formulations
Abstract. In this paper, we propose new adaptive local refinement (ALR) strategies for firstorder system least-squares (FOSLS) finite element in conjunction with algebraic multi...
J. H. Adler, Thomas A. Manteuffel, Stephen F. McCo...