Introduces the fundamentals of linear algebra in the context of computer science applications. Includes vector spaces, matrices, linear systems, and eigenvalues.

The teaching and learning of linear algebra have evolved significantly over recent decades, underpinned by diverse approaches ranging from theoretical expositions to dynamic, model-based ...

Students should ideally have taken the course Mathematical Methods (MA100) or equivalent, entailing intermediate-level knowledge of linear algebra, linear independence, eigenvalues and diagonalisation ...

Prom the point of view of numerical linear algebra, the main novelty of the fast randomized iteration schemes described in this article is that they have dramatically reduced operations and storage ...

Furthermore, we present a new algorithm and give some numerical results. The Journal of Computational Mathematics is published bi-monthly. It is an international journal covering all branches of ...

This is a 10-week bridge course that prepares students for the fundamentals of linear algebra as they are used in Applied Statistics courses.

Students should ideally have taken the course Mathematical Methods (MA100) or equivalent, entailing intermediate-level knowledge of linear algebra, linear independence, eigenvalues and diagonalisation ...