Numerical linear algebra is where rubber meets the road. This post collects some topics of interest to me. I aim to provide exposition better than standard textbooks whenever I can. Often times, ideas keep lying around deep inside 1000-page bibles.
An uncategorized list of references of high pedagogic value.
An Introduction to the Conjugate Gradient Method Without the Agonizing Pain by Jonathan Richard Shewchuk (1994)
Toeplitz and Circulant Matrices: A Review by Robert M. Gray (2006)
Scalable Inference for Structured Gaussian Process Models, Chapter 5 ^{1} by Yunus Saatçi (2011)
The Matrix Cookbook by Kaare Brandt Petersen, Michael Syskind Pedersen (2012)
Discovering Transforms: A Tutorial on Circulant Matrices, Circular Convolution, and the Discrete Fourier Transform by Bassam Bamieh (2018)
Numerical Linear Algebra by Lloyd N. Trefethen and David Bau, III (1997)
Numerical Optimization by Jorge Nocedal, Stephen J. Wright (2006)
Includes description, properties and an application of Kronecker-factored matrices. ↩