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CDC
2009
IEEE
180views Control Systems» more  CDC 2009»
13 years 11 months ago
Robustness analysis for Least Squares kernel based regression: an optimization approach
—In kernel based regression techniques (such as Support Vector Machines or Least Squares Support Vector Machines) it is hard to analyze the influence of perturbed inputs on the ...
Tillmann Falck, Johan A. K. Suykens, Bart De Moor
IJCNN
2008
IEEE
14 years 1 months ago
Fully complex-valued radial basis function networks for orthogonal least squares regression
— We consider a fully complex-valued radial basis function (RBF) network for regression application. The locally regularised orthogonal least squares (LROLS) algorithm with the D...
Sheng Chen, Xia Hong, Chris J. Harris
NN
2000
Springer
165views Neural Networks» more  NN 2000»
13 years 7 months ago
Construction of confidence intervals for neural networks based on least squares estimation
We present the theoretical results about the construction of confidence intervals for a nonlinear regression based on least squares estimation and using the linear Taylor expansio...
Isabelle Rivals, Léon Personnaz
ICML
1999
IEEE
14 years 8 months ago
Least-Squares Temporal Difference Learning
Excerpted from: Boyan, Justin. Learning Evaluation Functions for Global Optimization. Ph.D. thesis, Carnegie Mellon University, August 1998. (Available as Technical Report CMU-CS-...
Justin A. Boyan
ICASSP
2011
IEEE
12 years 11 months ago
Improved model-based spectral compressive sensing via nested least squares
This paper introduces a new algorithm for reconstructing signals with sparse spectrums from noisy compressive measurements. The proposed model-based algorithm takes the signal str...
Mahdi Shaghaghi, Sergiy A. Vorobyov