Publications of Stefan Kindermann

Articles in refereed journals

1. Simon Hubmer, Ekaterina Sherina, Stefan Kindermann, and Kemal Raik, A numerical comparison of some heuristic stopping rules for nonlinear Landweber iteration, Electron. Trans. Numer Anal., 57 (2022), pp.261-241.
2.  S. Kindermann, On the tangential cone condition for electrical impedance tomography, Electron. Trans. Numer Anal., 57 (2022), pp.17-34.https://etna.math.kent.edu/volumes/2021-2030/vol57/abstract.php?vol=57&pages=17-34
3. D. Gerth, B.Hofmann, C. Hofmann, S. Kindermann, The Hausdorff Moment Problme in the light of ill-posedness of type I, Eurasian Journal of Mathematical and Computer Applications 9, Issue 2 (2021), 57-87.
4. S. Kindermann, Optimal-order convergence of Nesterov acceleration for linear ill-posed problems. Inverse Problems, 37 (2021),  Art. 065002, 21 pages.
5. S. Kindermann and K. Raik,  Convergence of Heuristic Parameter Choice Rules for Convex Tikhonov Regularisation, SIAM J. Numer. Anal, 58, pp1773-1800, 2020.
6. S. Kindermann and K. Raik, A simplified L-curve as error estimator,  Electron. Trans. Numer Anal., 53 (2020), pp. 217--238.
7. Stefan Kindermann and Kemal Raik, Heuristic parameter choice rules for Tikhonov Regularisation with weakly bounded noise,  Numer Funkt Anal. Optim,  40 (2019), pp.~1373--1394.
8. B. Hofmann, S. Kindermann, P. Mathe, Penalty-based smoothness conditions in convex variational regularization, Journal if Inverse and Ill-posed Problems, 27 (2019), pp. 283-300.
9. S. Kindermann and S. Papacek, Optimization of the shape (and topology) of the initial conditions
   for diffusion parameter identification,  Computer and Mathematics with Applications, 2019. https://doi.org/10.1016/j.camwa.2019.01.025
10. U. Hämarik, U. Kangro, S. Kindermann,  and K. Raik, Semi-heuristic parameter choice rules for Tikhonov regularization with operator perturbation,  J. Inverse Ill-posed Problems, 27 (2019), pp. 117-131, doi 10.1515/jiip-2018-00622019.
11. S. Kindermann, A note on the approximate symmetry of Bregman distances, Jounal of Convex Analysis,  26 (2019), No 3, pp. 991-999.
12. T. Helin, S. Kindermann, J. Lethonen, R. Ramlau, Atmospheric turbulence profiling with unknown power spectral density,  Inverse Problems, Volume 34, Number 4  2018, Art Id 044002, 32 pages.
13. S. Kindermann, S. Pereverzyev Jr., Andrey Pilipenko, The quasi-optimality criterion in the linear functional strategy,  Inverse Problems,  Volume 34, Number 7, 2018, Art. Id. 075001, 24 pages.
14. X Wang, C. Navasca, S. Kindermann, On accelerating the regularized alternating least square algorithm for tensors, Electron. Trans. Numer. Anal., 48 (2018), pp1-14.
15. Stefan Kindermann, Convergence of the gradient method for ill-posed problems, Inv. Probl. Imaging, Volume 11, Issue 4, 2017, pp. 703-720
16. E. Lughofer, S. Kindermann, M. Pratama, J. de Jesus Rubio, Top-down sparse fuzzy inference system modelling from data with improved coverage, Int. J. Fuzzy Syst.m 2016.  DOI 10.1007/s40815-016-0271-0
17. T. Helin, S. Kindermann, D.  Saxenhuber, Towards analytical model optimization in atmospheric tomography, Math. Meth. Appl Sci, 40 (2017), pp1153-1169 Preprint: http://arxiv.org/abs/1511.07223
18. S. Kindermann, Projection methods for ill-posed problems revisited, accepted for Comput Method Appl. Math. , 16 (2) 2015, pp. 257--276. Preprint: http://arxiv.org/abs/1507.03364
19. S. Kindermann, Convex Tikhonov regularization in Banach spaces: new results on convergence rates, J. Inverse Ill-posed Problems,  24 (3), 2015, pp. 341--350.  
20. S. Kindermann, S. Papacek
    On data space selection and data processing for parameter identifciation in a reaction diffusion model based on FRAP experiments, Abstract and Applied Analysis, vol. 2015, Article ID 859849, 17 pages, doi:10.1155/2015/859849, 2015
21. E. Lughofer, C. Cernuda, S. Kindermann, M. Pratama,
    Gerneralized smart evolving fuzzy systems,
    Evolving Systems,  6 (4), 269-292, 2015,
22. S. Kindermann, A. Leitao,
    Convergence rates for Kaczmarz type regularization methods,
    Inverse Problems and Imaging, 8, 149-172, 2014
23. S. Kindermann, L. Mutimbu, and E. Resmerita,
    A numerical study of heuristic parameter choice rules for total variation regularization,
    J. Inv. Ill-posed Probl., 22, pp. 63-94, 2014.
24. D. Lengani, S. Kindermann, T. Selic, A. Marn, F. Heitmeir,
    Measurement and decomposition of periodic flow structures downstream of a test turbine,
    Experiments in Fluids, 55 (1), Art. 1632, 2014, DOI 10.1007/s00348-013-1632-1
25. S. Kindermann and C. Navasca
    New algorithms for tensor decomposition based on a reduced functional,
    Num. Linear Algebra Appl,  21, pp. 340-374,  2014,  DOI: 10.1002/nla.1875
26. S. Kindermann
    Discretization independent convergence rates for noise level-free parameter choice rules in the regularization of ill-conditioned problems,
    ETNA, 40, pp 58-81, 2013
    Link to Pdf
27. N. Li., S. Kindermann and C. Navasca
    Some convergence results on the Regularized Alternating Least-Squares method for tensor decomposition,
    Linear Algebra Appl., 438, No 2, pp  796–812,  2013
28. S. Kindermann, A. Neubauer and R. Ramlau
    A singular value decomposition for the Shack-Hartman based wavefront reconstruction,
    J. Comp. Appl. Math, 236, No. 1, pp 2186-2199, 2012.
29. V. Isakov and S. Kindermann
    Subspaces of stability in the Cauchy-Problem for the Helmholtz equation
    Meth. Appl Anal., Vol. 18, No. 1, pp 1-30, 2011
30. S. Kindermann
    Convergence Analysis for minimization based noise level-free parameter choice rules for linear ill-posed problems
    ETNA, Vol. 38, pp. 233-257, 2011,
    Link to Pdf
31. S. Kindermann and P.A. Mayer
    On the calibration of local jump-diffusion asset price models
    Finance and Stochastics, 15, No. 4, pp 685–724 , 2011
32. B. Hofmann and S. Kindermann
    On the degree of Ill-posedness for linear problems with non-compact operators
    Methods of Applications and Analysis, Vol 17, No 4, pp. 445-462, 2010
33. A. Neubauer, T. Hein, B. Hofmann, S. Kindermann and U. Tautenhahn
    Improved and extended results for enhanced convergence rates for Tikhonov regularization in Banach spaces,
    Appl. Anal. Vol. 89, No. 11, pp. 1729--1744, 2010
34. E. Lughofer, S. Kindermann
    SparseFIS: Data-driven learning of fuzzy systems with sparsity constraints
    IEEE Trans. Fuzzy Sys. Vol 18, No.2 pp 396--411. 2010
35. S. Kindermann and M. Janicki
    The heat transform and its use in thermal identification problems
    Electr. Trans. Numer. Anal. (ETNA), Vol. 35, pp 164--184, (2009)
36. M. Janicki and S. Kindermann.
    Recovering temperature dependence of heat transfer coefficient in electronic circuits
    Inv. Prob. Sci. Eng., 1741-5985, Vol. 17, (8) pp. 1129--1142, (2009)
37. S. Kindermann.
    Bounded variation regularization using line sections
    Numer. Func. Anal. Optim. vol. 30, pp 259-288, (2009)
38. F. Bauer and S. Kindermann.
    Recent results on the quasi-optimality principle
    J. Inv. Ill-posed Probl. 17, Issue 1 (2009), 5-18.
39. L. He, S. Kindermann, M. Sini
    Reconstruction of shapes and impedance function using few farfield measurements,
    J. Comp. Phys, Vol 228, Issue 3, (2009), 717-730.
40. M. Janicki, S. Kindermann, P. Pietrzak and A. Napieralski
    Estimation of local temperature dependent heat transfer coefficient for dynamic thermal analysis of electronic circuits,
    Journal of Physics: Conference Series 135 (2008) 012053
41. V. Capasso, H. W. Engl and S. Kindermann
    Parameter identification in a random environment exemplified by a multiscale model of crystal growth.
    SIAM Mulit. Mod. Sim. 7, Nr. 2, pp 814-841 (2008)
42. S. Kindermann and A. Neubauer
    On the convergence of the quasi-optimality criterion for (iterated) Tikhonov regularization
    Inv. Prob. Imag., 2, Nr. 2, pp 291-299, 2008
43. F. Bauer and S. Kindermann.
    The quasi-optimality criterion for classical inverse problems
    Inverse Problems, 24, 035002 (20pp) 2008.
44. S. Kindermann, P. Mayer, H-J. Albrecher, and H. W. Engl.
    Identification of the local speed function in a levy model for option pricing.
    J. Int. Eq. Appl, 20(2), 161-200, 2008.
45. S. Rupitsch, S. Kindermann and B. Zagar
    Estimation of the surface normal velocity of high frequency utrasound transducers.
    IEEE, Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, 2007, Vol 55, No. 1, pp 225-235
46. S. Rupitsch, S. Kindermann and B. Zagar
    Solution of a non-linear inverse problem to identify the surface normal verlocity of ultrasound transducers.
    e & i (7-8), 2007.
47. S. Kindermann and A. Leitao.
    Regularization by dynamic programing.
    J. Inv. Ill-posed Probl., 15, pp. 295--310, 2007.
48. S. Kindermann and R. Ramlau.
    Surrogate functionals and thresholding for inverse interface problems.
    J. Inv. Ill-posed Probl., 15, pp. 387-402, 2007.
49. S. Kindermann and A. Leitao.
    On regularization methods based on dynamic programming techniques.
    Appl. Anal., 86(5), pp. 611--632, 2007.
50. S. Kindermann and A. Leitao.
    On regularization methods for inverse problems of dynamic type.
    Numer. Funct. Anal. Optimi., 27(2),pp. 139--160, 2006.
51. S. Kindermann and C. Navasca.
    Optimal control as a regularization method for ill-posed problems.
    J. Inv. Ill-posed Prob., 14, pp. 685-703, 2006
52. S. Kindermann, S. Osher, and J. Xu.
    Denoising by BV-duality.
    J. Sci. Comp, 28, pp. 411--444, 2006.
53. H.W. Engl, A. Hofinger, and S. Kindermann.
    Convergence rates in the Prokhorov metric for assessing uncertainty in ill-posed problems.
    Inverse Problems (21), pp. 399--412, 2005.
54. S. Kindermann, S. Osher, and P. Jones.
    Deblurring and denoising of images by nonlocal functionals.
    SIAM, Mult. Mod. Sim., 4(4), pp. 1091--1115, 2005.
55. S. Kindermann and A. Neubauer.
    Parameter identification by regularization for surface representation via the moving grid aproach.
    SIAM, J. Control Optim., (4), pp. 1416-1430, 2003.
56. S. Kindermann and A. Neubauer.
    Estimation of discontinuous parameters of elliptic partial differential equations by regularization for surface representations.
    Inverse Problems, 17, pp. 789--803, 2001.
57. S. Kindermann and A. Neubauer.
    Regularization for surface representations of discontinuous solutions of linear ill-posed problems.
    Numer. Funct. Anal. Optim., 22(1&2),pp. 79--105, 2001.
58. V. Iskaov and S. Kindermann.
    Identification of the diffusion coefficient in a one-dimensional parabolic equation.
    Inverse Problems, 16, pp. 665--680, 2000.
59. S. Kindermann and A. Neubauer.
    Identification of discontinuous parameters by regularization for curve representations.
    Inverse Problems, 15, pp. 1559--1572, 1999.
60. S. Kindermann.
    Convergence of the Hilbert uniqueness method via Tikhonov regularization.
    J. Optimization Theory Appl., 103(3),pp. 657--673, 1999.
61. S. Kindermann.
    A numerical investigation of Newton-type methods applied to a parabolic inverse problem. J. Inverse Ill-Posed Probl., 7(6), pp. 541--560, 1999.

Books

• Cullen M., Freitag M.A., Kindermann S., Scheichl R. (eds), Large Scale Inverse problems
  Radon Series on Computational ans Applied Mathematics 13, de Gruyter, Berlin, 2013.

Book Chapter

• S. Kindermann, H.K. Pikkarainen.
  Regularisation of inverse problems and its application to the clibration of option price models
  in Advanced Financial Modelling, H. Albrecher, W.J. Runggaldier, W. Schachermayer, eds., Radon Series on Computationl and Applied Mathematics 8, de Gruyter, Berlin, 2009.

Conference Proceedings

• D. Gerth and S. Kindermann, The Kurdyka-\L{}ojasiewicz inequality as regularity condition, to appear in Inverse Problems and Related Topics, J. Cheng, S. LU, M. Yamamoto, eds., Springer, Shanghai, 2020, pp. 257-274.
• C. Matonoha, S. Papacek, and S. Kindermann, Disk vs. annulus: on the bleaching pattern optimization for FRAP experiments, accepted for High Perfomance Computing in Science and Engineering, 2018, Springer, pp 160-173.
• C. Matonoha, S. Papacek, and S. Kindermann, On the optimization of initial conditions for a model parameter estimation, Proceedings of Seminar "Programs and Algorithms of Numerical Mathematics 18" Janoc nad Nisou 19.-24.6.2016, p. 73-80.
• S. Papacek, S. Kindermann
  On Optimization of FRAP Experiments: Model-Based Sensitivity Analysis Approach, IWBBIO, 2016.
• S. Papacek, J. Jablonsky, R. Kana, C. Matonoha, S. Kindermann
  FRAP and FLIP: Two sides of the same coin ?, IWBBIO 2015,
• S. Papacek, J. Jablonsky, R. Kana, C. Matonoha, S. Kindermann
  From data processing to experimental design and back again: a parameter identification problem based on FRAP Images
  ICPESE 2015, 13
• M. Janicki S. Kindermann, A. Napieralski.
  Investigation of cicuit thermal models based on the transient thermal response spectra
  15th Intern. Conf on MIXDES 2008, pp 337-342
• E. Lughofer, S. Kindermann
  Rule weight optimization and feature selection in Fuzzy Systems with sparsity constrains
  in Proceedings of the IFSA/EUSFLAT 2009 conference, Number 950-956, 2009.
• C. Navasca, L. De Lathauwer, S. Kindermann.
  Swamp Reducing Technique for Tensor Decomposition,
  In Proceedings of the 16th European Signal Processing Conference (EUSIPCO 2008), Lausanne, 2008.
• E. Lughofer and S. Kindermann.
  Improving the Robustness of Data-Driven Fuzzy-Systems with Regularization.
  Proc. of the IEEE World Congress on Computational Intelligence (WCCI), 2008, Hongkong, pp 703-709, 2008.
• S. Kindermann and A. Neubauer.
  On the estimation of discontinuous solutions of parameter identification problems.
  In J. Cheng and M. Yamamoto, editors, 2nd International Conference on Inverse Problems: Recent Theoretical Developments and Numerical Approaches, pages 83--92, Bristol, 2005. Journal of Physics.
• H. Gu and S. Kindermann.
  Solution analysis of pdes related to the Mumford-Shah functional with symbolic computations.
  In Proceedings of the 7th International Conference of Computational Structure Technology, Lisboa, 2004. Civil Comp Press.

Technical Reports

• A. Hofinger and S. Kindermann.
  Assessing Uncertainty in Nonlinear Inverse Problems with the Metric of Ky Fan.
  Technical report, University Linz SFB F013, 2006.
• S. Kindermann and S. Osher.
  Saddle point formulation for a cartoon-texture decomposition.
  Technical report, CAM-Report 05-42, UCLA, 2005.
• S. Kindermann.
  A new iterative regularization method using an equation of hamilton-jacobi type.
  Technical report, University Linz SFB F013, July 2003.
• S. Kindermann and A. Neubauer.
  Each BV-function is representable by an H1-curve.
  Technical Report 1/1999, Industrial Mathematics Institute, University of Linz, 1999.

Not yet published

1. S. Kindermann, Inversion formulas for the linearized impedance tomography problem, rejected

In Prep. 

1. J.Duintjer Tebbens, S. Kindermann, S.Papacek, Pharmacodynamic Modeling of Xenobiotic CYP3A4 Encyme, in prep, 2022.
2. Faoumata Sanogo, Carmeliza Navasca, S. Kindermann, Tensor deblurring and denoising using total variation, in prep. 2022.