This article addresses the inference of physics models from data, from the perspectives of
inverse problems and model reduction. These fields develop formulations that integrate data …

Large linear systems of saddle point type arise in a wide variety of applications throughout
computational science and engineering. Due to their indefiniteness and often poor spectral …

The objective of this monograph is the treatment of a general class of nonlinear variational
problems of the form min y∈ Y, u∈ U ƒ (y, u) subject to e (y, u)= 0, g (y, u)∈ K, 0.0. 1 where …

The problem of finding good preconditioners for the numerical solution of indefinite linear
systems is considered. Special emphasis is put on preconditioners that have a 2× 2 block …

Large-scale optimization of systems governed by partial differential equations (PDEs) is a
frontier problem in scientific computation. Reduced quasi-Newton sequential quadratic …

This is a book on Optimal Control Problems (OCPs): how to formulate them, how to set up a
suitable mathematical framework for their analysis, how to approximate them numerically …

Some first and second order algorithmic approaches for the solution of PDE‐constrained
optimization problems are reviewed. An optimal control problem for the stationary Navier …

The problem of recovering a parameter function based on measurements of solutions of a
system of partial differential equations in several space variables leads to a number of …

A new class of preconditioners for the iterative solution of the linear systems arising from
interior point methods is proposed. For many of these methods, the linear systems are …

This book gives an introduction to iterative methods and preconditioning for solving
discretized elliptic partial differential equations (PDEs) and optimal control problems …