Many advances in the development of Krylov subspace methods for the iterative solution of
linear systems during the last decade and a half are reviewed. These new developments …

This paper surveys an important class of methods that combine iterative projection methods
and variational regularization methods for large-scale inverse problems. Iterative methods …

Parameter Estimation and Inverse Problems, Third Edition, is structured around a course at
New Mexico Tech and is designed to be accessible to typical graduate students in the …

The L-curve is a log-log plot of the norm of a regularized solution versus the norm of the
corresponding residual norm. It is a convenient graphical tool for displaying the trade-off …

We present a novel technique for the determination of resistivity structures associated with
arbitrary surface topography. The approach represents a triple-grid inversion technique that …

Numerical solution of ill-posed problems is often accomplished by discretization (projection
onto a finite dimensional subspace) followed by regularization. If the discrete problem has …

This paper develops a fast method for solving linear SVMs with L 2 loss function that is
suited for large scale data mining tasks such as text classification. This is done by modifying …

Lanczos-hybrid regularization methods have been proposed as effective approaches for
solving largescale ill-posed inverse problems. Lanczos methods restrict the solution to lie in …

Many numerical methods for the solution of linear ill-posed problems apply Tikhonov
regularization. This paper presents a new numerical method, based on Lanczos …

The numerical and computational aspects of the overlap formalism in lattice quantum
chromodynamics are extremely demanding due to a matrix–vector product that involves the …