In this program
- Sparse matrix formats
- Memory-aware implementations
- Parallel and distributed linear algebra (overview)
- Least squares
- Ridge regression at scale
- Randomized numerical linear algebra (sketching, introduction)
- Applications in data science and imaging
- PDE discretizations
Large-scale and applied problems
Randomized numerical linear algebra (sketching, introduction)
Numerical linear algebra · STEM / applied
Topic
Randomized numerical linear algebra (sketching, introduction)
Graduate Numerical Linear Algebra — scope drawn from open NLA notes (e.g. Trefethen/Bau-style OER mirrors) and typical US graduate NLA syllabi.