Rapidly Convergent Recursive Solution of Quadratic Operator Equations.
Reduktionsverfahren für Differenzengleichungen bei Randwertaufgaben I.
Regular Splittings and Monotone Iteration Functions.
Regularisierung schlecht gestellter Probleme durch Projektionsverfahren.
Regularity Theorems and Optimal Errors Estimates for Linear Parabolic Cauchy Problems.
Regularization in state space
Regularization of nonlinear ill-posed problems by exponential integrators
The numerical solution of ill-posed problems requires suitable regularization techniques. One possible option is to consider time integration methods to solve the Showalter differential equation numerically. The stopping time of the numerical integrator corresponds to the regularization parameter. A number of well-known regularization methods such as the Landweber iteration or the Levenberg-Marquardt method can be interpreted as variants of the Euler method for solving the Showalter differential...
Regularization properties of Tikhonov regularization with sparsity constraints.
Relaxing convergence conditions for the Jarratt method.
Remark on a Newton-Moser type method
Remark on an iterative formula
Remarks on inflated mappings
Résolution des équations semilinéaires avec la partie linéaire à noyau de dimension infinie via des applications A-propres [Book]
Resolvent estimates in controllability theory and applications to the discrete wave equation
We briefly present the difficulties arising when dealing with the controllability of the discrete wave equation, which are, roughly speaking, created by high-frequency spurious waves which do not travel. It is by now well-understood that such spurious waves can be dealt with by applying some convenient filtering technique. However, the scale of frequency in which we can guarantee that none of these non-traveling waves appears is still unknown in general. Though, using Hautus tests, which read the...
Results on controlling the residuals of perturbed Newton-like methods on Banach spaces with a convergence structure.
Risk bounds for new M-estimation problems
In this paper, we consider a new framework where two types of data are available: experimental data Y1,...,Yn supposed to be i.i.d from Y and outputs from a simulated reduced model. We develop a procedure for parameter estimation to characterize a feature of the phenomenon Y. We prove a risk bound qualifying the proposed procedure in terms of the number of experimental data n, reduced model complexity and computing budget m. The method we present is general enough to cover a wide range of applications....
Runge-Kutta-Verfahren mit festen und variablen Parametern zur Lösung von Systemen gewöhnlicher Differentialgleichungen 1. Ordnung