with being the (tall thin) matrix from the ML-cup dataset by Prof. Micheli, , and is a random vector. (A1) is thin QR factorization via Householder reflectors, cf. also Lecture 10. (A2) is a variant ...
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 distributed-memory parallel implementation of the sparsified QR factorization algorithm using the TaskTorrent runtime system. This repository provides efficient QR factorization for large sparse ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback