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2020
1 Grasmair, Markus.
Source Conditions for Non-Quadratic Tikhonov Regularization. Numerical Functional Analysis and Optimization 2020 s. 1352-1372
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2018
2 Grasmair, Markus; Klock, Timo; Naumova, Valeriya.
Adaptive multi-penalty regularization based on a generalized Lasso path. Applied and Computational Harmonic Analysis 2018 s. 1-26
NTNU Untitled
 
3 Grasmair, Markus; Li, Housen; Munk, Axel.
Variational multiscale nonparametric regression: Smooth functions. Annales de l'I.H.P. Probabilites et statistiques 2018 ;Volum 54.(2) s. 1058-1097
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4 Grunert, Katrin; Holden, Helge; Grasmair, Markus.
On the Equivalence of Eulerian and Lagrangian Variables for the Two-Component Camassa–Holm System. I: Current Research in Nonlinear Analysis: In Honor of Haim Brezis and Louis Nirenberg. Springer Nature 2018 ISBN 978-3-319-89799-8. s. 157-201
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2017
5 Bauer, Martin; Eslitzbichler, Markus; Grasmair, Markus.
Landmark-guided elastic shape analysis of human character motions. Inverse Problems and Imaging 2017 ;Volum 11.(4) s. 601-621
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6 Grasmair, Markus.
A nonlocal, nonconvex functional for coherence enhancing image restoration. Applied Inverse Problems; 2017-05-29 - 2017-06-02
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7 Grasmair, Markus.
A nonlocal, nonconvex functional for coherence enhancing image restoration. Challenges in the Preservation of Structure; 2017-06-27 - 2017-06-30
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8 Grasmair, Markus.
Convergence Rates for Multiresolution based Regularisation Methods. Statistics Meets Friends; 2017-11-29 - 2017-12-01
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9 Grasmair, Markus.
Convergence Rates for Multiresolution based Regularisation Methods. MAD-Stat. Seminar; 2017-12-07 - 2017-12-07
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10 Grasmair, Markus.
Multi-penalty regularization for sparse support recovery. Bayesian and Nonlinear Inverse Problems; 2017-08-28 - 2017-09-01
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11 Grasmair, Markus.
Multiscale statistical regularisation for inverse problems in imaging. Applied Inverse Problems; 2017-05-29 - 2017-06-02
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2016
12 Grasmair, Markus.
Local parameter adaptation in imaging applications by means of multiresolution. Imaging, Vision and Learning based on Optimization and PDEs; 2016-08-29 - 2016-09-01
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13 Grasmair, Markus.
Local parameter adaptation in imaging applications by means of multiresolution. Current and future trends in computed tomography; 2016-09-15 - 2016-09-16
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14 Grasmair, Markus.
Multiparameter sparse regularisation for unmixing problems. Inverse Problems: Modeling and Simulation; 2016-05-23 - 2016-05-28
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15 Grasmair, Markus.
The multiresolution norm for statistical inverse problems. Inverse Problems: Modeling and Simulation; 2016-05-23 - 2016-05-28
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16 Grasmair, Markus; Naumova, Valeriya.
Conditions on optimal support recovery in unmixing problems by means of multi-penalty regularization. Inverse Problems 2016 ;Volum 32.(10)
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2015
17 Bauer, Martin; Grasmair, Markus; Kirisits, Clemens.
Optical Flow on Moving Manifolds. SIAM Journal of Imaging Sciences 2015 ;Volum 8.(1) s. 484-512
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18 Grasmair, Markus.
Multiscale nonparametric regression. Chemnitz Symposium on Inverse Problems; 2015-09-17 - 2015-09-18
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19 Grasmair, Markus.
Source Conditions for Non-smooth Sparse Regularisation. Applied Inverse Problems 2015; 2015-05-25 - 2015-05-29
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20 Grasmair, Markus.
Sparse Regularisation for Inverse Problems. Research Seminar; 2015-05-07 - 2015-05-07
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2014
21 Beretta, Elena; Grasmair, Markus; Muszkieta, Monika; Scherzer, Otmar.
A variational algorithm for the detection of line segments. Inverse Problems and Imaging 2014 ;Volum 8.(2) s. 389-408
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22 Grasmair, Markus.
Bregman distance, source conditions, and variational inequalities in Tikhonov regularisation. Chemnitz Symposium on Inverse Problems; 2014-09-18 - 2014-09-19
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23 Grasmair, Markus.
Multiresolution in Statistical Inverse Problems. Inverse Problems: Modeling and Simulation; 2014-05-26 - 2014-05-31
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24 Grasmair, Markus.
Optical Flow on Moving Manifolds. Workshop on Advances in Mathematical Imaging; 2014-11-24 - 2014-11-26
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25 Grasmair, Markus.
Optical Flow on Moving Manifolds. Anysotropy 2014; 2014-10-16 - 2014-10-18
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26 Lyckander, Ingvild; Grasmair, Markus; Halvorsen-Weare, Elin Espeland; Hasle, Geir.
A Hybrid Metaheuristic for a multi-objective Mixed Capacitated General Routing Problem. The third meeting of the EURO Working Group on Vehicle Routing and Logistics Optimization (VeRoLog 2014); 2014-06-22 - 2014-06-25
NTNU SINTEF Untitled
 
2013
27 Bauer, Martin; Fidler, Thomas; Grasmair, Markus.
Local Uniqueness of the Circular Integral Invariant. Inverse Problems and Imaging 2013 ;Volum 7.(1) s. 107-122
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28 Dong, Guozhi; Grasmair, Markus; Kang, Sung Ha; Scherzer, Otmar.
Scale and Edge Detection with Topological Derivatives. Lecture Notes in Computer Science (LNCS) 2013 ;Volum 7893. s. 404-415
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29 Grasmair, Markus.
The Multi-resolution Norm for Non-parametric Regression and Inverse Problems. Séminaire Pluridisciplinaire d'Optimisation de Toulouse; 2013-11-04 - 2013-11-04
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30 Grasmair, Markus.
Topological Derivatives and Image Segmentation. 84. Annual Meeting of the International Association of Applied Mathematics and Mechanics; 2013-03-18 - 2013-03-22
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31 Grasmair, Markus.
Variational inequalities and higher order convergence rates for Tikhonov regularisation on Banach spaces. Journal of Inverse and Ill-Posed Problems 2013 ;Volum 21.(3) s. 379-394
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32 Grasmair, Markus; Muszkieta, Monika; Scherzer, Otmar.
An approach to the minimization of the Mumford-Shah functional using Gamma-convergence and topological asymptotic expansion. Interfaces and free boundaries (Print) 2013 ;Volum 15.(2) s. 141-166
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33 Grasmair, Markus; Scherzer, Otmar; Vanhems, Anne.
Nonparametric instrumental regression with non-convex constraints. Inverse Problems 2013 ;Volum 29.(3) s. -
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2012
34 Fidler, Thomas; Grasmair, Markus; Scherzer, Otmar.
Shape reconstruction with a priori knowledge based on integral invariants. SIAM Journal of Imaging Sciences 2012 ;Volum 5.(2) s. 726-745
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35 Frick, Klaus; Grasmair, Markus.
Regularization of linear ill-posed problems by the augmented Lagrangian method and variational inequalities. Inverse Problems 2012 ;Volum 28.(10)
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36 Grasmair, Markus.
Convergence rates for Tikhonov regularisation on Banach spaces. Oberwolfach Reports 2012 ;Volum 9.(4) s. 3102-3103
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2011
37 Grasmair, Markus.
Linear convergence rates for Tikhonov regularization with positively homogeneous functionals. Inverse Problems 2011 ;Volum 27.(7)
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38 Grasmair, Markus.
Well-posedness classes for sparse regularization. Communications in Mathematical Sciences 2011 ;Volum 9.(4) s. 1129-1141
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39 Grasmair, Markus; Haltmeier, Markus; Scherzer, Otmar.
Necessary and sufficient conditions for linear convergence of l1-regularization. Communications on Pure and Applied Mathematics 2011 ;Volum 64.(2) s. 161-182
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40 Grasmair, Markus; Haltmeier, Markus; Scherzer, Otmar.
The residual method for regularizing ill-posed problems. Applied Mathematics and Computation 2011 ;Volum 218.(6) s. 2693-2710
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2010
41 Alexandrov, Theodore; Becker, Michael; Deininger, Sören-Oliver; Ernst, Günther; Wehder, Liane; Grasmair, Markus; von Eggeling, Ferdinand; Thiele, Herbert; Maass, Peter.
Spatial segmentation of imaging mass spectrometry data with edge-preserving image denoising and clustering. Journal of Proteome Research 2010 ;Volum 9.(12) s. 6535-6546
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42 Elbau, Peter; Grasmair, Markus; Lenzen, Frank; Scherzer, Otmar.
Evolution by non-convex functionals. Numerical Functional Analysis and Optimization 2010 ;Volum 31.(4) s. 489-517
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43 Grasmair, Markus.
Generalized Bregman distances and convergence rates for non-convex regularization methods. Inverse Problems 2010 ;Volum 26.(11)
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44 Grasmair, Markus.
Non-convex sparse regularisation. Journal of Mathematical Analysis and Applications 2010 ;Volum 365.(1) s. 19-28
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45 Grasmair, Markus; Haltmeier, Markus; Scherzer, Otmar.
Sparsity in Inverse Geophysical Problems. I: Handbook of Geomathematics. Springer 2010 ISBN 978-3-642-01545-8. s. 763-784
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46 Grasmair, Markus; Lenzen, Frank.
Anisotropic total variation filtering. Applied Mathematics and Optimization 2010 ;Volum 62.(3) s. 323-339
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2009
47 Grasmair, Markus.
Locally Adaptive Total Variation Regularization. Lecture Notes in Computer Science (LNCS) 2009 ;Volum 5567. s. 331-342
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48 Grasmair, Markus.
Well-posedness and convergence rates for sparse regularization with sublinear l^q penalty term. Inverse Problems and Imaging 2009 ;Volum 3.(3) s. 383-387
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49 Scherzer, Otmar; Grasmair, Markus; Grossauer, Harald; Haltmeier, Markus; Lenzen, Frank.
Variational methods in imaging. Springer 2009 (ISBN 978-0-387-30931-6) 320 s. Applied mathematical sciences(167)
NTNU Untitled
 
2008
50 Fidler, Thomas; Grasmair, Markus; Scherzer, Otmar.
Identifiability and reconstruction of shapes from integral invariants. Inverse Problems and Imaging 2008 ;Volum 2.(3) s. 341-354
NTNU Untitled
 
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