We present optimal parallel QR factorization algorithms with reduced communication overhead. QR factorization is widely applied to solve various problems in numerical linear algebra. Our focus is on ...

Scammers are increasingly exploiting QR codes to trick people into revealing financial information or installing malicious software on their devices. The FBI has recently issued a warning about a ...

Dozens of machine learning algorithms require computing the inverse of a matrix. Computing a matrix inverse is conceptually easy, but implementation is one of the most challenging tasks in numerical ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of computing a matrix inverse using the Newton iteration algorithm. Compared to other algorithms, Newton ...

QR-decomposition based QR-algorithm for eigenvalues evaluation of symmetric matrix with real values with OpenMP directives for parallelization of computations for multi-core systems ...

Abstract: We consider computing the QR factorization with column pivoting (QRCP) for a tall and skinny matrix, which has important applications including low-rank approximation and rank determination.

A version of this document that discusses the complex valued case can be found here . This material is probably best suited to students who have had a course in linear algebra already. Given a SPD ...