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.

Abstract: Since 2017, NVIDIA GPUs have been equipped with specialized units known as Tensor Cores, which demonstrate remarkable efficiency in processing matrix multiplications (GEMMs). Beyond GEMMs, ...

The code implements and tests four QR factorization methods: Classical GramSchmidt, Modified Gram-Schmidt, Householder, and Givens rotations which can be executed and reproduced within the Jupyter ...

My linear algebra textbook (Advanced Linear Algebra,Steven Roman, pg. 217) says for QR factorization: any real or complex matrix is amenable to a decomposition A = QR, with Q orthonormal columns and R ...

ABSTRACT: This paper presents an approach that directly utilizes the Hessian matrix to investigate the existence and uniqueness of global solutions for the ECQP problem. The novel features of this ...

Least-squares reverse time migration (LSRTM) has become a popular research topic and has been practically applied in recent years. LSRTM can generate preferable images with high signal-to-noise ratio ...