29 citations · 31 across the 4 of their papers we have counts for
7 papers · 1 filter
Graph and distributed extensions of the Douglas-Rachford method
Kristian Bredies, Enis Chenchene, Emanuele Naldi
In this paper, we propose several graph-based extensions of the Douglas-Rachford splitting (DRS) method to solve monotone inclusion problems involving the sum of maximal monoto…
A hybrid proximal generalized conditional gradient method and application to total variation parameter learning
Kristian Bredies, Enis Chenchene, Alireza Hosseini
In this paper we present a new method for solving optimization problems involving the sum of two proper, convex, lower semicontinuous functions, one of which has Lipschitz continuo…
Degenerate Preconditioned Proximal Point algorithms
Kristian Bredies, Enis Chenchene, Dirk A. Lorenz +1
In this paper we describe a systematic procedure to analyze the convergence of degenerate preconditioned proximal point algorithms. We establish weak convergence results under mild…
Higher-order total variation approaches and generalisations
Kristian Bredies, Martin Holler
Over the last decades, the total variation (TV) evolved to one of the most broadly-used regularisation functionals for inverse problems, in particular for imaging applications. Whe…
Tensor-Free Proximal Methods for Lifted Bilinear/Quadratic Inverse Problems with Applications to Phase Retrieval
Robert Beinert, Kristian Bredies
We propose and study a class of novel algorithms that aim at solving bilinear and quadratic inverse problems. Using a convex relaxation based on tensorial lifting, and applying fir…
Sparsity of solutions for variational inverse problems with finite-dimensional data
Kristian Bredies, Marcello Carioni
In this paper we characterize sparse solutions for variational problems of the form , where is a locally convex space, is a…