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M5: Convex Analysis and Inverse Problems In the last decades, techniques and methods of convex analysis have increasingly been employed in inverse problems, in particular in the context of nonlinear Tikhonov regularization approaches. This has been mainly motivated by the striking success of nonsmooth convex regularization functionals, such as L1-type norms, in order to approach problems originating in real-life applications. Elements of convex analysis have been also determinant when using Bregman distances as misfit functionals in the setting of Banach spaces. Not least, convex optimization algorithms have enabled the efficient numerical solution of the resulting regularized optimization problems, which are typically nonsmooth and of large scale. We want to bring together researchers who are employing methods specific to convex analysis in the analysis and numerics of ill-posed inverse problems to present and discuss their latest results. Organizers: Radu Ioan Boț, University of Vienna, Austria, This email address is being protected from spambots. You need JavaScript enabled to view it. Kristian Bredies, University of Graz, Austria, This email address is being protected from spambots. You need JavaScript enabled to view it. Invited Speakers (in alphabetical order): Agnieszka Badenska, Warsaw Institute of Technology, Poland, This email address is being protected from spambots. You need JavaScript enabled to view it. Towards Quaternion Compressed Sensing Ewa Bednarczuk, Polish Academy of Sciences, Poland, This email address is being protected from spambots. You need JavaScript enabled to view it. On Variants of Best Approximation Iterative Schemes for Solving Maximally Monotone Inclusion Problems with Applications Radu Ioan Boț, University of Vienna, Austria, This email address is being protected from spambots. You need JavaScript enabled to view it. The Proximal Alternating Directional Method of Multipliers in the Nonconvex Setting: Convergence Analysis and Rates Emilie Chouzenoux, Université Paris-Est, France, This email address is being protected from spambots. You need JavaScript enabled to view it. Proximal Interior Point Algorithm For Large Scale Image Processing Problems Ernö Robert Csetnek, University of Vienna, Austria, This email address is being protected from spambots. You need JavaScript enabled to view it. Approaching Nonsmooth Optimization Problems Through Continuous and Discrete Proximal-Type Algorithms Guillaume Garrigos, Italian Institute of Technology, Genova, Italy, This email address is being protected from spambots. You need JavaScript enabled to view it. Rates in Convex Optimization and Links with Inverse Problems Erich Kobler, Graz University of Technology, Austria, This email address is being protected from spambots. You need JavaScript enabled to view it. Learning Convex Regularizers for Image Reconstruction Dirk Lorenz, Braunschweig University of Technology, Germany, This email address is being protected from spambots. You need JavaScript enabled to view it. Total Variation Denoising with Additional Gradient Information Ignace Loris, Vrije Universiteit Brussel, Belgium, This email address is being protected from spambots. You need JavaScript enabled to view it. On Nested Primal-Dual Iterations for the Solution of Ill-Posed Inverse Problems Yurii Malitskyi, University of Göttingen, Germany, This email address is being protected from spambots. You need JavaScript enabled to view it. Primal-Dual Algorithm for Linearly Constrained Optimization Problem Orsola Rath-Spivack, University of Cambridge, UK, This email address is being protected from spambots. You need JavaScript enabled to view it., A New Adaptive Multiplicative Regularization Elena Resmerita, University of Klagenfurt, Austria, This email address is being protected from spambots. You need JavaScript enabled to view it. The Least Error Method for Sparse Solution Reconstruction Krzysztof Rutkowski, Warsaw Institute of Technology, Poland, This email address is being protected from spambots. You need JavaScript enabled to view it. On Differential Variational Inequalities Associated with Maximally Monotone Inclusion Problems Tuomo Valkonen, University of Liverpool, United Kingdom, This email address is being protected from spambots. You need JavaScript enabled to view it. Preconditioned Proximal-Point Methods with Applications to Inverse Problems Silvia Villa, Politecnico di Milano, Italy, This email address is being protected from spambots. You need JavaScript enabled to view it. Proximal Algorithms as Iterative Regularization Methods
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