DR.
GODELA SCHERER
Departamento de Cómputo Científico y Estadística
Universidad Simón Bolívar, Venezuela
and Dept. of Mathematics,
Reading University, U.K.
godela@compuserve.com

 Basic mathematical aspects and numerical algorithms
for the linear least squares: singular value decomposition (SVD), QR,
and Lanczos methods.
 Ill conditioning: characterization and examples. Regularization
methods.
 Survey of the classical methods, separable nonlinear
problems.
 Large problems
Recommended background: Basic knowledge of
numerical linear algebra and computing skills.
Course Material: There will be course notes.
References for the course are:
[1] Björck, Å.; "Numerical Methods for Least Squares Problems",
SIAM 1996.
[2] Golub, G. and Pereyra, V.; "Separable nonlinear least squares:
the variable projection method and its applications." Topical Review,
Inverse Problems 19:R1R26 (2003).
