Course Syllabus

ai_policy.jpg18.335-Syllabus.pdf

Approximate list of topics:

Root finding: bisection, secant and newtons methods, fixed point iteration
Floating point arithmetic, numerical stability, condition numbers
System solving: Brief linalg review, QR, LU, pivoting, iterative refinement
Regression: Normal equations, SVD, pseudoinverse, projections
Iterative methods: Gauss-Seidel, SOR, Kaczmarz
Eigenvalue algorithms: power method / subspace iteration, QR algorithm, implicit QR, Jacobi
Krylov methods: sparsity, arnoldi/Lanczos, GMRES/MINRES, CG
Other: Gaussian quadrature, discretization, numerical optimization

Course Summary:

Course Summary
Date Details Due