# Iterative regularization for constrained minimization formulations of nonlinear inverse problems

arXiv: https://arxiv.org/abs/2101.05482 · HTML: https://mlsanity.com/paper/2101.05482/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 14 Jan 2021.

## Built on by (most cited first, 1 of 1)

- [Generalization Error Bounds for Picard-Type Operator Learning in Nonlinear Parabolic PDEs](https://mlsanity.com/paper/2605.10277/) (2026)

## Abstract (arXiv)

In this paper we the formulation of inverse problems as constrained minimization problems and their iterative solution by gradient or Newton type. We carry out a convergence analysis in the sense of regularization methods and discuss applicability to the problem of identifying the spatially varying diffusivity in an elliptic PDE from different sets of observations. Among these is a novel hybrid imaging techology known as impedance acoustic tomography, for which we provide numerical experiments.