In this paper we characterize sparse solutions for variational problems of the form\min _ u ∈
X ϕ (u)+ F (A u) min u∈ X ϕ (u)+ F (A u), where X is a locally convex space, AA is a linear …

Nonlinearity parameter tomography leads to the problem of identifying a coefficient in a
nonlinear wave equation (such as the Westervelt equation) modeling ultrasound …

We develop a dynamic generalized conditional gradient method (DGCG) for dynamic
inverse problems with optimal transport regularization. We consider the framework …

The objective of this work is to quantify the reconstruction error in sparse inverse problems
with measures and stochastic noise, motivated by optimal sensor placement. To be useful in …

We present a systematic approach to the optimal placement of finitely many sensors in order
to infer a finite-dimensional parameter from point evaluations of the solution of an associated …

A generalized conditional gradient method for minimizing the sum of two convex functions,
one of them differentiable, is presented. This iterative method relies on two main ingredients …

A class of generalized conditional gradient algorithms for the solution of optimization
problem in spaces of Radon measures is presented. The method iteratively inserts …

Inverse problems for line sources radiating inside a homogeneous magneto-dielectric
cylinder are investigated. The developed algorithms concern the determination of the …

Extracting information from nonlinear measurements is a fundamental challenge in data
analysis. In this work, we consider separable inverse problems, where the data are modeled …

This work is concerned with the optimal control problems governed by a 1D wave equation
with variable coefficients and the control spaces $\mathcal M_T $ of either measure-valued …