Lectures related to Truncated CG: Conjugate Gradients

Covers the analysis of linear systems, focusing on methods such as Jacobi and Richardson for solving linear equations.

Covers the concept of convex functions and their applications in optimization problems.

Covers normed spaces, dual spaces, Banach spaces, Hilbert spaces, weak and strong convergence, reflexive spaces, and the Hahn-Banach theorem.

Explores linear algebra basics, emphasizing matrix representations of transformations and the importance of choosing appropriate bases.

Explains linear independence, bases, and dimension in vector spaces, including the importance of the order of vectors in a basis.

Covers the basics of linear mapping and coordinate systems.