1 citations · 2 across the 22 of their papers we have counts for
23 papers
Stability results for regularized least-squares problems via generalized Hessian expressions and monotone generalized equations
Leo Smulansky, Tim Hoheisel, Tran T. A. Nghia
We study perturbation and stability properties of solution mappings associated with convex regularized least-squares problems. We first establish an implicit function theorem for g…
A Scale-Shape Dual Newton Method for Entropic Least Squares
Nicholas Barnfield, James V. Burke, Michael P. Friedlander +1
We give a damped inexact Newton method for entropy-regularized least-squares on the nonnegative orthant that converges globally at a linear rate with iteration comp…
Augmented Lagrangian methods for fully convex composite optimization
Alberto De Marchi, Tim Hoheisel, Patrick Mehlitz
This paper is concerned with augmented Lagrangian methods for the treatment of fully convex composite optimization problems. We extend the classical relationship between augmented…
Discrete and Continuous Difference of Submodular Minimization
George Orfanides, Tim Hoheisel, Marwa El Halabi
Submodular functions, defined on continuous or discrete domains, arise in numerous applications. We study the minimization of the difference of two submodular (DS) functions, over…
Data-Driven Priors in the Maximum Entropy on the Mean Method for Linear Inverse Problems
Matthew King-Roskamp, Rustum Choksi, Tim Hoheisel
We establish the theoretical framework for implementing the maximumn entropy on the mean (MEM) method for linear inverse problems in the setting of approximate (data-driven) priors…
Lipschitz stability of least-squares problems regularized by functions with -cone reducible conjugates
Ying Cui, Tim Hoheisel, Tran T. A. Nghia +1
In this paper, we study Lipschitz continuity of the solution mappings of regularized least-squares problems for which the convex regularizers have (Fenchel) conjugates that are $\m…