CMOR 430: SYST OF EQNS & UNCONST OPTIM
Spring 2026 · Section 001 · CRN 22924
Iterative methods for linear systems of equations including Krylov subspace methods, including the conjugate gradient method and GMRES; gradient and Newton-like methods for unconstrained optimization and nonlinear least squares problems; Newton and Newton-like methods for nonlinear systems of equations; techniques for improving the global convergence of these algorithms; implementation of these methods in Matlab or Python; applications to example problems in science and engineering. Cross-list: CMOR 530. Recommended Prerequisite(s): (CAAM 453 or CMOR 422)
- Credits
- 3
- Instructors
- Matthias Heinkenschloss