In this project it is used a Machine Learning model based on a method called Extreme Learning, with the employment of L2-regularization. In particular, a comparison was carried out between: (A1) which ...

This MATLAB project demonstrates the use of QR factorization to identify linearly dependent columns in a matrix and then applies the Gram-Schmidt process to compute an orthonormal basis for the ...

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 ...

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.