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Organizing Committee
VI PanAmerican Workshop
Computational Science Programs



Dr. Godela Scherer- Course Outline

Departamento de Cómputo Científico y Estadística
Universidad Simón Bolívar, Venezuela
and Dept. of Mathematics,
Reading University, U.K.

  • 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 non-linear 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:R1-R26 (2003).