Prof. Dr. Michael Hintermüller
Profil
Forschungsthemen22
CH 12: Erweiterte Abbildung durch Kernspinresonanz: Fingerabdruck und geometrische Quantifikation
Quelle ↗Förderer: Einstein Stiftung Berlin Zeitraum: 06/2017 - 12/2018 Projektleitung: Prof. Dr. Michael Hintermüller
DFG-Forschungszentrum "Mathematik für Schlüsseltechnologien - MATHEON": Control of phase separation phenomena with applications to structure formation during cooling of binary alloys and phase inversion processes in polymetric membrane production.
Quelle ↗Förderer: DFG sonstige Programme Zeitraum: 10/2008 - 05/2010 Projektleitung: Prof. Dr. Michael Hintermüller
EXC 2046 1 AG Hintermüller EF3-3
Quelle ↗Förderer: DFG Exzellenzstrategie Cluster Zeitraum: 01/2019 - 06/2022 Projektleitung: Prof. Dr. Michael Hintermüller
EXC 2046 1 AG Hintermüller EF3-5
Quelle ↗Förderer: DFG Exzellenzstrategie Cluster Zeitraum: 01/2019 - 09/2022 Projektleitung: Prof. Dr. Michael Hintermüller
EXC 2046/1: Equilibria for Energy Markets with Transport (AG Hintermüller, TP AA4-3)
Quelle ↗Förderer: DFG Exzellenzstrategie Cluster Zeitraum: 01/2019 - 12/2021 Projektleitung: Prof. Dr. Michael Hintermüller
EXC 2046/1: Transition
Quelle ↗Förderer: DFG Exzellenzinitiative Cluster Zeitraum: 01/2019 - 09/2019 Projektleitung: Prof. Dr. Michael Hintermüller
EXC 2046: Berlin Mathematics Research Center (MATH+)
Quelle ↗Förderer: DFG Exzellenzstrategie Cluster Zeitraum: 01/2019 - 12/2024 Projektleitung: Prof. Dr. Caren Tischendorf, Prof. Dr. Michael Hintermüller, Prof. Dr. Max Klimm, Prof. Dr. Dörte Kreher, Prof. Chris Wendl, Prof. Dr. Bettina Rösken-Winter, Prof. Dr. rer. nat. Dr. h.c. Edda Klipp
Formoptimierung
Quelle ↗Förderer: Wirtschaftsunternehmen / gewerbliche Wirtschaft Zeitraum: 12/2015 - 06/2016 Projektleitung: Prof. Dr. Michael Hintermüller
Formoptimierung
Quelle ↗Förderer: Wirtschaftsunternehmen / gewerbliche Wirtschaft Zeitraum: 05/2011 - 09/2011 Projektleitung: Prof. Dr. Michael Hintermüller
Formoptimierung II
Quelle ↗Förderer: Wirtschaftsunternehmen / gewerbliche Wirtschaft Zeitraum: 10/2013 - 04/2014 Projektleitung: Prof. Dr. Michael Hintermüller
Forschungsstipendium Konstantinos Papafitsoros
Quelle ↗Förderer: Alexander von Humboldt-Stiftung Zeitraum: 05/2015 - 04/2017 Projektleitung: Prof. Dr. Michael Hintermüller
Freie Randwertprobleme und Level-Set-Verfahren
Quelle ↗Förderer: DFG Sachbeihilfe Zeitraum: 04/2015 - 03/2018 Projektleitung: Prof. Dr. Michael Hintermüller
Fully adaptive and integrated numerical methods for the simulation and control of variable density multiphase flows governed by diffuse interface models
Quelle ↗Förderer: DFG Sachbeihilfe Zeitraum: 07/2013 - 06/2016 Projektleitung: Prof. Dr. Michael Hintermüller
Mathematical Modeling, Analysis, and Optimization of Strained Germanium-Microbridges
Quelle ↗Förderer: Einstein Stiftung Berlin Zeitraum: 06/2014 - 05/2017 Projektleitung: Prof. Dr. Michael Hintermüller
Optimal Design and Control of Optofluidic Solar Steerers and Concentrators
Quelle ↗Förderer: Einstein Stiftung Berlin Zeitraum: 06/2014 - 05/2017 Projektleitung: Prof. Dr. Michael Hintermüller
Optimale Steuerung von Elektrobenetzung auf dielektrischen Medien
Quelle ↗Förderer: DFG Sachbeihilfe Zeitraum: 02/2014 - 12/2016 Projektleitung: Prof. Dr. Michael Hintermüller
OT6: Optimierung und Steuerung von Electrowetting auf Nichtleitern für digitale Micro-Fluidelemente in neuen Technologien
Quelle ↗Förderer: Einstein Stiftung Berlin Zeitraum: 06/2017 - 12/2018 Projektleitung: Prof. Dr. Michael Hintermüller
SFB-TRR 154/1: Mehrzieloptimierung mit Gleichgewichtsrestriktionen am Beispiel von Gasmärkten (TP B02)
Quelle ↗Förderer: DFG Sonderforschungsbereich Zeitraum: 10/2014 - 06/2022 Projektleitung: Prof. Dr. Michael Hintermüller
SPP Optimierung mit partiellen Differentialgleichungen
Quelle ↗Förderer: DFG Sachbeihilfe Zeitraum: 10/2009 - 12/2014 Projektleitung: Prof. Dr. Michael Hintermüller
Unterstützung: 6th International Conference on Complementarity Probelms 2014
Quelle ↗Förderer: Einstein Stiftung Berlin Zeitraum: 07/2014 - 10/2014 Projektleitung: Prof. Dr. Michael Hintermüller
VA: 6th International Conference on Complementarity Problems 2014
Quelle ↗Förderer: DFG sonstige Programme Zeitraum: 08/2014 - 10/2014 Projektleitung: Prof. Dr. Michael Hintermüller
VA: Internationale Konferenz über Mathematik und Bildanalyse 2018
Quelle ↗Zeitraum: 01/2018 - 04/2018 Projektleitung: Prof. Dr. Michael Hintermüller
Mögliche Industrie-Partner10
Stand: 26.4.2026, 19:48:44 (Top-K=20, Min-Cosine=0.4)
- 123 Treffer62.0%
- Workshop Reliable Methods and Mathematical ModelingP62.0%
- Workshop Reliable Methods and Mathematical Modeling
- 66 Treffer61.4%
- Interfaces in opto-electronic thin film multilayer devicesP61.4%
- Interfaces in opto-electronic thin film multilayer devices
- DYnamic control in hybrid plasmonic NAnopores: road to next generation multiplexed single MOlecule detectionP58.7%
- DYnamic control in hybrid plasmonic NAnopores: road to next generation multiplexed single MOlecule detection
- 62 Treffer58.4%
- INTeractive RObotics Research NetworkP58.4%
- INTeractive RObotics Research Network
- 61 Treffer58.4%
- INTeractive RObotics Research NetworkP58.4%
- INTeractive RObotics Research Network
- 99 Treffer57.2%
- Embodied Audition for RobotSP57.2%
- Embodied Audition for RobotS
- 164 Treffer57.2%
- EU: Bottom-Up Generation of atomicalLy Precise syntheTIc 2D MATerials for High Performance in Energy and Electronic Applications – A Multi-Site Innovative Training Action (ULTIMATE)P57.2%
- EU: Simulation in Multiscale Physical and Biological Systems (STIMULATE)P55.8%
- EU: Bottom-Up Generation of atomicalLy Precise syntheTIc 2D MATerials for High Performance in Energy and Electronic Applications – A Multi-Site Innovative Training Action (ULTIMATE)
- 82 Treffer57.2%
- EU: Bottom-Up Generation of atomicalLy Precise syntheTIc 2D MATerials for High Performance in Energy and Electronic Applications – A Multi-Site Innovative Training Action (ULTIMATE)P57.2%
- EU: Bottom-Up Generation of atomicalLy Precise syntheTIc 2D MATerials for High Performance in Energy and Electronic Applications – A Multi-Site Innovative Training Action (ULTIMATE)
- 86 Treffer57.2%
- EU: Bottom-Up Generation of atomicalLy Precise syntheTIc 2D MATerials for High Performance in Energy and Electronic Applications – A Multi-Site Innovative Training Action (ULTIMATE)P57.2%
- EU: Bottom-Up Generation of atomicalLy Precise syntheTIc 2D MATerials for High Performance in Energy and Electronic Applications – A Multi-Site Innovative Training Action (ULTIMATE)
- 129 Treffer57.2%
- EU: Bottom-Up Generation of atomicalLy Precise syntheTIc 2D MATerials for High Performance in Energy and Electronic Applications – A Multi-Site Innovative Training Action (ULTIMATE)P57.2%
- Integrated Self-Assembled SWITCHable Systems and Materials: Towards Responsive Organic Electronics – A Multi-Site Innovative Training Action (iSwitch)P54.5%
- EU: Bottom-Up Generation of atomicalLy Precise syntheTIc 2D MATerials for High Performance in Energy and Electronic Applications – A Multi-Site Innovative Training Action (ULTIMATE)
Publikationen25
Top 25 nach Zitationen — Quelle: OpenAlex (BAAI/bge-m3 embedded für Matching).
SIAM Journal on Optimization · 978 Zitationen · DOI
International audience
SIAM Journal on Scientific Computing · 153 Zitationen · DOI
In this paper, a primal-dual algorithm for total bounded variation (TV)--type image restoration is analyzed and tested. Analytically it turns out that employing a global $\boldsymbol{L}^s$-regularization, with $1 < s \leq 2$, in the dual problem results in a local smoothing of the TV-regularization term in the primal problem. The local smoothing can alternatively be obtained as the infimal convolution of the $\ell_r$-norm, with $r^{-1} + s^{-1} = 1$, and a smooth function. In the case $r = s = 2$, this results in Gauss-TV--type image restoration. The globalized primal-dual algorithm introduced in this paper works with generalized derivatives, converges locally at a superlinear rate, and is stable with respect to noise in the data. In addition, it utilizes a projection technique which reduces the size of the linear system that has to be solved per iteration. A comprehensive numerical study ends the paper.
SIAM Journal on Applied Mathematics · 146 Zitationen · DOI
It is demonstrated that the predual for problems with total bounded variation regularization terms can be expressed as a bilaterally constrained optimization problem. Existence of a Lagrange multiplier and an optimality system are established. This allows us to utilize efficient optimization methods developed for problems with box constraints in the context of bounded variation formulations. Here, in particular, the primal-dual active set method, considered as a semismooth Newton method, is analyzed, and superlinear convergence is proved. As a by-product we obtain that the Lagrange multiplier associated with the box constraints acts as an edge detector. Numerical results for image denoising and zooming/resizing show the efficiency of the new approach.
Journal of Mathematical Imaging and Vision · 141 Zitationen · DOI
SIAM Journal on Optimization · 124 Zitationen · DOI
This research is devoted to the numerical solution of constrained optimal control problems governed by elliptic partial differential equations. The main purpose is a comparison between a recently developed Moreau--Yosida-based active set strategy involving primal and dual variables and two implementations of interior point algorithms.
SIAM Journal on Applied Mathematics · 120 Zitationen · DOI
The problem of segmentation of a given image using the active contour technique is considered. An abstract calculus to find appropriate speed functions for active contour models in image segmentation or related problems based on variational principles is presented. The speed method from shape sensitivity analysis is used to derive speed functions which correspond to gradient or Newton-type directions for the underlying optimization problem. The Newton-type speed function is found by solving an elliptic problem on the current active contour in every time step. Numerical experiments comparing the classical gradient method with Newton's method are presented.
SIAM Journal on Optimization · 108 Zitationen · DOI
Path-following methods for primal-dual active set strategies requiring a regularization parameter are introduced. Existence of a primal-dual path and its differentiability properties are analyzed. Monotonicity and convexity of the primal-dual path value function are investigated. Both feasible and infeasible approximations are considered. Numerical path-following strategies are developed and their efficiency is demonstrated by means of examples.
ESAIM Control Optimisation and Calculus of Variations · 107 Zitationen · DOI
We present an a posteriori error analysis of adaptive finite element approximations of distributed control problems for second order elliptic boundary value problems under bound constraints on the control. The error analysis is based on a residual-type a posteriori error estimator that consists of edge and element residuals. Since we do not assume any regularity of the data of the problem, the error analysis further invokes data oscillations. We prove reliability and efficiency of the error estimator and provide a bulk criterion for mesh refinement that also takes into account data oscillations and is realized by a greedy algorithm. A detailed documentation of numerical results for selected test problems illustrates the convergence of the adaptive finite element method.
SIAM Journal on Imaging Sciences · 106 Zitationen · DOI
A nonconvex variational model is introduced which contains the $\ell_q$-``norm,” $q\in (0,1)$, of the gradient of the underlying image in the regularization part together with a least squares--type data fidelity term which may depend on a possibly spatially dependent weighting parameter. Hence, the regularization term in this functional is a nonconvex compromise between the minimization of the support of the reconstruction and the classical convex total variation model. In the discrete setting, existence of a minimizer is proved, and a Newton-type solution algorithm is introduced and its global as well as local superlinear convergence toward a stationary point of a locally regularized version of the problem is established. The potential nonpositive definiteness of the Hessian of the objective during the iteration is handled by a trust-region--based regularization scheme. The performance of the new algorithm is studied by means of a series of numerical tests. For the associated infinite dimensional model an existence result based on the weakly lower semicontinuous envelope is established, and its relation to the original problem is discussed.
SIAM Journal on Optimization · 99 Zitationen · DOI
An optimal control problem governed by an elliptic variational inequality is studied. The feasible set of the problem is relaxed, and a path–following-type method is used to regularize the constraint on the state variable. First order optimality conditions for the relaxed-regularized subproblems are derived, and convergence of stationary points with respect to the relaxation and regularization parameters is shown. In particular, C- and strong stationarity as well as variants thereof are studied. The subproblems are solved by using semismooth Newton methods. The overall algorithmic concept is provided, and its performance is discussed by means of examples, including problems with bilateral constraints and a nonsymmetric operator.
Feasible and Noninterior Path‐Following in Constrained Minimization with Low Multiplier Regularity
2006SIAM Journal on Control and Optimization · 98 Zitationen · DOI
Primal‐dual path‐following methods for constrained minimization problems in function space with low multiplier regularity are introduced and analyzed. Regularity properties of the path are proved. The path structure allows us to define approximating models, which are used for controlling the path parameter in an iterative process for computing a solution of the original problem. The Moreau–Yosida regularized subproblems of the new path‐following technique are solved efficiently by semismooth Newton methods. The overall algorithmic concept is provided, and numerical tests (including a comparison with primal‐dual path‐following interior point methods) for state constrained optimal control problems show the efficiency of the new concept.
SIAM Journal on Imaging Sciences · 91 Zitationen · DOI
Image restoration based on an $\ell^1$-data-fitting term and edge preserving total variation regularization is considered. The associated nonsmooth energy minimization problem is handled by utilizing Fenchel duality and dual regularization techniques. The latter guarantee uniqueness of the dual solution and an efficient way for reconstructing a primal solution, i.e., the restored image, from a dual solution. For solving the resulting primal-dual system, a semismooth Newton solver is proposed and its convergence is studied. The paper ends with a report on restoration results obtained by the new algorithm for salt-and-pepper or random-valued impulse noise including blurring. A comparison with other methods is provided as well.
Advances in Computational Mathematics · 83 Zitationen · DOI
International Journal of Computer Mathematics · 80 Zitationen · DOI
In this paper, the automated spatially dependent regularization parameter selection framework for multi-scale image restoration is applied to total generalized variation (TGV) of order 2. Well-posedness of the underlying continuous models is discussed and an algorithm for the numerical solution is developed. Experiments confirm that due to the spatially adapted regularization parameter, the method allows for a faithful and simultaneous recovery of fine structures and smooth regions in images. Moreover, because of the TGV regularization term, the adverse staircasing effect, which is a well-known drawback of the total variation regularization, is avoided.
IEEE Transactions on Image Processing · 76 Zitationen · DOI
A two-phase image restoration method based upon total variation regularization combined with an L(1)-data-fitting term for impulse noise removal and deblurring is proposed. In the first phase, suitable noise detectors are used for identifying image pixels contaminated by noise. Then, in the second phase, based upon the information on the location of noise-free pixels, images are deblurred and denoised simultaneously. For efficiency reasons, in the second phase a superlinearly convergent algorithm based upon Fenchel-duality and inexact semismooth Newton techniques is utilized for solving the associated variational problem. Numerical results prove the new method to be a significantly advance over several state-of-the-art techniques with respect to restoration capability and computational efficiency.
SIAM Journal on Control and Optimization · 75 Zitationen · DOI
In this paper, the optimal boundary control of a time-discrete Cahn--Hilliard--Navier--Stokes system is studied. A general class of free energy potentials is considered which, in particular, includes the double-obstacle potential. The latter homogeneous free energy density yields an optimal control problem for a family of coupled systems, which result from a time discretization of a variational inequality of fourth order and the Navier--Stokes equation. The existence of an optimal solution to the time-discrete control problem as well as an approximate version is established. The latter approximation is obtained by mollifying the Moreau--Yosida approximation of the double-obstacle potential. First order optimality conditions for the mollified problems are given, and in addition to the convergence of optimal controls of the mollified problems to an optimal control of the original problem, first order optimality conditions for the original problem are derived through a limit process. The newly derived stationarity system is related to a function space version of C-stationarity.
Goal-Oriented Adaptivity in Control Constrained Optimal Control of Partial Differential Equations
2008SIAM Journal on Control and Optimization · 74 Zitationen · DOI
Dual-weighted goal-oriented error estimates for a class of pointwise control constrained optimal control problems for second order elliptic partial differential equations are derived. It is demonstrated that the constraints give rise to a primal-dual weighted error term representing the mismatch in the complementarity system due to discretization. The paper also contains a posteriori error estimators for the $L^2$-norm of the error in the state and in the adjoint state.
SIAM Journal on Numerical Analysis · 69 Zitationen · DOI
An adjustment scheme for the regularization parameter of a Moreau–Yosida-based regularization, or relaxation, approach to the numerical solution of pointwise state constrained elliptic optimal control problems is introduced. The method utilizes error estimates of an associated finite element discretization of the regularized problems for the optimal selection of the regularization parameter in dependence on the mesh size of discretization and error estimates for the approximation error due to regularization. The theoretical results are verified numerically.
Multiphase Image Segmentation and Modulation Recovery Based on Shape and Topological Sensitivity
2009Journal of Mathematical Imaging and Vision · 68 Zitationen · DOI
Control and Cybernetics · 68 Zitationen
A level set based shape and topology optimization approach to electrical impedance tomography (EIT) problems with piecewise constant con- ductivities is introduced. The proposed solution algorithm is initialized by using topological sensitivity analysis. Then it relies on the notion of shape derivatives to update the shape of the domains where the conductivity takes its different values.
Journal of Mathematical Imaging and Vision · 68 Zitationen · DOI
Computational Optimization and Applications · 66 Zitationen · DOI
SIAM Journal on Control and Optimization · 65 Zitationen · DOI
In this paper we study the distributed optimal control for the Cahn–Hilliard system. A general class of free energy potentials is allowed which, in particular, includes the double-obstacle potential. The latter potential yields an optimal control problem of a parabolic variational inequality which is of fourth order in space. We show the existence of optimal controls to approximating problems where the potential is replaced by a mollified version of its Moreau–Yosida approximation. Corresponding first-order optimality conditions for the mollified problems are given. For this purpose a new result on the continuous Fréchet differentiability of superposition operators with values in Sobolev spaces is established. Besides the convergence of optimal controls of the mollified problems to an optimal control of the original problem, we also derive first-order optimality conditions for the original problem by a limit process. The newly derived stationarity system corresponds to a function space version of C-stationarity.
Earth and Planetary Science Letters · 59 Zitationen · DOI
SIAM Journal on Imaging Sciences · 58 Zitationen · DOI
The minimization of a functional composed of a nonsmooth and nonadditive regularization term and a combined $L^1$ and $L^2$ data-fidelity term is proposed. It is shown analytically and numerically that the new model has noticeable advantages over popular models in image processing tasks. For the numerical minimization of the new objective, subspace correction methods are introduced which guarantee the convergence and monotone decay of the associated energy along the iterates. Moreover, an estimate of the distance between the outcome of the subspace correction method and the global minimizer of the nonsmooth objective is derived. This estimate and numerical experiments for image denoising, inpainting, and deblurring indicate that in practice the proposed subspace correction methods indeed approach the global solution of the underlying minimization problem.
Kooperationen4
Bestätigte Forscher↔Partner-Paare aus HU-FIS — Gold-Standard-Positive für das Matching.
EXC 2046: Berlin Mathematics Research Center (MATH+)
university
EXC 2046: Berlin Mathematics Research Center (MATH+)
university
EXC 2046: Berlin Mathematics Research Center (MATH+)
other
EXC 2046: Berlin Mathematics Research Center (MATH+)
research_institute
Stammdaten
Identität, Organisation und Kontakt aus HU-FIS.
- Name
- Prof. Dr. Michael Hintermüller
- Titel
- Prof. Dr.
- Fakultät
- Mathematisch-Naturwissenschaftliche Fakultät
- Institut
- Institut für Mathematik
- Arbeitsgruppe
- Angewandte Mathematik
- Telefon
- +49 30 2093-45322
- HU-FIS-Profil
- Quelle ↗
- Zuletzt gescrapt
- 26.4.2026, 01:06:17