5 papers
Blind error estimation for CUR approximation
Lorenzo Lazzarino, Katherine J. Pearce, Nathaniel Pritchard
Low-rank approximation is a fundamental tool for scalable matrix computations. While such approximations have classically been formed via the truncated SVD, recent advances in rand…
Reducing acquisition time and radiation damage: data-driven subsampling for spectro-microscopy
Maike Meier, Lorenzo Lazzarino, Boris Shustin +2
Spectro-microscopy is an experimental technique which can be used to observe spatial variations in chemical state and changes in chemical state over time or under experimental cond…
Efficient error estimators for Generalized Nyström
Lorenzo Lazzarino, Katherine J. Pearce, Nathaniel Pritchard
Randomized algorithms in numerical linear algebra have proven to be effective in ameliorating issues of scalability when working with large matrices, efficiently producing accurate…
Preconditioned normal equations for solving discretised partial differential equations
Lorenzo Lazzarino, Yuji Nakatsukasa, Umberto Zerbinati
This paper explores preconditioning the normal equation for non-symmetric square linear systems arising from PDE discretization, focusing on methods like CGNE and LSQR. The concept…
Matrix perturbation analysis of methods for extracting singular values from approximate singular subspaces
Lorenzo Lazzarino, Hussam Al Daas, Yuji Nakatsukasa
Given (orthonormal) approximations and to the left and right subspaces spanned by the leading singular vectors of a matrix , we discuss methods to approx…