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» Recovery of sparse perturbations in Least Squares problems
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ICML
2008
IEEE
14 years 6 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
IWANN
2005
Springer
13 years 11 months ago
Load Forecasting Using Fixed-Size Least Squares Support Vector Machines
Based on the Nystr¨om approximation and the primal-dual formulation of Least Squares Support Vector Machines (LS-SVM), it becomes possible to apply a nonlinear model to a large sc...
Marcelo Espinoza, Johan A. K. Suykens, Bart De Moo...
SIAMMAX
2010
116views more  SIAMMAX 2010»
13 years 15 days ago
Structured Total Maximum Likelihood: An Alternative to Structured Total Least Squares
Abstract. Linear inverse problems with uncertain measurement matrices appear in many different applications. One of the standard techniques for solving such problems is the total l...
Amir Beck, Yonina C. Eldar
SIAMMAX
2010
92views more  SIAMMAX 2010»
13 years 15 days ago
Estimating the Backward Error in LSQR
We propose practical stopping criteria for the iterative solution of sparse linear least squares (LS) problems. Although we focus our discussion on the algorithm LSQR of Paige and ...
Pavel Jiránek, David Titley-Péloquin
SIAMSC
2010
120views more  SIAMSC 2010»
13 years 4 months ago
Simultaneously Sparse Solutions to Linear Inverse Problems with Multiple System Matrices and a Single Observation Vector
Abstract. A problem that arises in slice-selective magnetic resonance imaging (MRI) radiofrequency (RF) excitation pulse design is abstracted as a novel linear inverse problem with...
Adam C. Zelinski, Vivek K. Goyal, Elfar Adalsteins...