Prof. Dr.
Sergei Pereverzyev
Senior Fellow
Inverse Problems and Mathematical Imaging
Contact
Email: Sergei.Pereverzyev(at)oeaw.ac.at
Telephone: +43 732 2468 5215
Biographical sketch
- born on April 30, 1955, in Dnipropetrovsk, Ukraine; married, one son
- 1977: Degree in Mathematics (Diploma with honors and the Prize of the Ministry of Higher Education), Dnipropetrovsk
- 1980: Doctorate, Kiev
- 1989: Habilitation for Mathematics, Moscow
- 2000: International Prize for Achievement in Information-Based Complexity
FORMER AND CURRENT POSITIONS
- 1981/03: Scientific staff member of the Institute of Mathematics, Ukrainian Acad. of Sci.
- 1994: Visiting professor at the Department of Mathematics at the Beijing Normal University (China)
- 1994: Visiting professor at the Department of Computer Sciences (temporary C4-position) at the University of Kaiserslautern (Germany)
- 1999/00: Visiting professor at the Department of Mathematics (temporary C4-position) at the University of Kaiserslautern (Germany)
- 2002/03: Visiting professor at the Department of Mathematics (temporary C4-position) at the University of Kaiserslautern (Germany)
- Since September 2003: Research Scientist in the group "Inverse Problems" at the RICAM
Professional Service
- Member of Working Group 1.1 "Continuous Algorithms and Complexity" of the International Federation for Information Processing (IFIP)
- Member of Working Group "Inverse Problems in Geodesy" of the International Association of Geodesy (IAG)
- Member of the Editorial board of "Journal of Complexity", Elsevier Science
Research interests
- Inverse and ill-posed problems, Functional Analysis, Approximation Theory, Complexity Theory
Publications
Journal Publication (67)
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Holzleitner, Markus; Pereverzyev, Sergei V.; Zellinger, Werner (2024) Domain Generalization by Functional Regression. Numerical Functional Analysis and Optimization.
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Zellinger, Werner; Kindermann, Stefan; Sergei, Pereverzyev (2023) Adaptive learning of density ratios in RKHS. Journal of Machine Learning Research, Bd. 24 (1004), S. 1-28.
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Yuanyuan Li, Shuai Lu, Peter Mathé, Sergei V. Pereverzyev (2023) Two-layer networks with the ( ext {ReLU}^k) activation function: Barron spaces and derivative approximation. Numerische Mathematik, Bd. 155, S. 1-25.
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Mark Žic, Sergiy Pereverzyev (2023) Application of self-adapting regularization, machine learning tools and limits in Levenberg-Marquardt algorithm to solve CNLS problem. Journal of Electroanalytical Chemistry, Bd. 939, S. 117420.
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Zic, M. Kunaver and Z. Rojec and V. Subotic and S. Pereverzyev and M. (2022) Extraction of Distribution Function of Relaxation Times by using DRT-RBLM Tools: A New Approach to Combine Levenberg-Marquardt Algorithm and Radial Basis Functions for Discretization Basis. Journal of The Electrochemical Society, Bd. 169 (11), S. 110529.
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Zic, M.; Vlasic, L.; Subotic, V; Pereverzyev, S.; Fajfar, I et al. [..] (2022) Extraction of Distribution Function of Relaxation Times by using Levenberg-Marquardt Algorithm: A New Approach to Apply a Discretization Error Free Jacobian Matrix. J. Electrochem. Soc., Bd. 169 (3), S. ARTN 030508.
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Elke R. Gizewski, Lukas Mayer, Bernhard A. Moser, Duc Hoan Nguyen, Sergiy Pereverzyev Jr., Sergei V. Pereverzyev, Natalia Shepeleva, Werner Zellinger (2022) On a regularization of unsupervised domain adaptation in RKHS. Applied and Computational Harmonic Analysis, Bd. 57, S. 201-227.
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Hrushikesh Mhaskar, Sergei Pereverzyev, Maria Dorothea Van Der Walt (2021) A Function Approximation Approach to the Prediction of Blood Glucose Levels. Fontiers in Applied Mathematics and Statistics, Bd. 7, S. 13.
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H N. Mhaskar, S V. Pereverzyev and M. D. Van Der Walt (2021) A function approximation approach to the prediction of blood glucose levels. Frontiers in Applied Mathematics and Statistics, Bd. 11, S. 10.
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Zic, Mark; Fajfar, Iztok; Subotic, Vanja; Pereverzyev, Sergei; Kunaver, Matevz (2021) Investigation of Electrochemical Processes in Solid Oxide Fuel Cells by Modified Levenberg-Marquardt Algorithm: A New Automatic Update Limit Strategy. PROCESSES, Bd. 9 (1), S. ARTN 108.
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Shuai Lu, Peter Mathe, Sergei Pereverzyev (2020) Randomized matrix approximation to enhance regularized projection schemes in inverse problems. Inverse Problems, Bd. 36, S. 20.
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Shuai Lu, Peter Mathé and Sergei V. Pereverzev (2020) Randomized matrix approximation to enhance regularized projection schemes ininverse problems. Inverse Problems, Bd. 36 (8), S. 085013 (20pp).
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M. Krasnoschok, S. Pereverzyev, S.V. Siryk, N. Vasylyeva (2020) Determination of the fractional order in semilinear subdiffusion equations. Fractional Calculus and Applied Analysis, Bd. 23 (3), S. 694 - 722 <'https://www.degruyter.com/view/journals/fca/fca-overview.xml'>.
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Mark Žica, Vanja Subotićb, Sergei Pereverzyev, Iztok, Fajfard (2020) Solving CNLS problems using Levenberg-Marquardt algorithm: A new fitting strategy combining limits and a symbolic Jacobian matrix. Journal of Electroanalytical Chemistry, Bd. 866 (1), S. 114171.
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Žic, Mark, Subotic, Vanja, Pereverzev, Sergei V., Fajfar, Iztok (2020) Solving CNLS problems using Levenberg-Marquardt algorithm: A new fitting strategy combining limits and a symbolic Jacobian matrix. Journal of Electroanalytical Chemistry, Bd. 866 (1), S. 114171.
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Mark Žic, Sergiy Pereverzyev Jr., Vanja Subotić, Sergei Pereverzyev (2020, online: 2019) Adaptive multi-parameter regularization approach to construct the distribution function of relaxation times. International Journal on Geomathematics, Bd. 11 (2), S. 1-23.
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Mark Žic, Sergei Pereverzyev (2019) Optimizing noisy CNLS problems by using Nelder-Mead algorithm: A new method to compute simplex step efficiency. Journal of Electroanalytical Chemistry, Bd. 851, S. 113439.
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Hrushikesh Mhaskar, Sergei Pereverzyev, Vasyl Semenov and Evgeniya Semenova (2019) Data Based Construction of Kernels for Semi-supervised Learning with Less Labels. Fontiers in Applied Mathematics and Statistics, Bd. 4, S. 12.
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Sergei V. Pereverzyev, Shuai Lu, Peter Mathé (2018) Balancing principle in supervised learning for a general regularization scheme. Applied and Computational Harmonic Analysis, Bd. 45, S. 26.
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Kriukova, Galyna; Pereverzyev, Sergiy, Jr.; Tkachenko, Pavlo (2017) Nystrom type subsampling analyzed as a regularized projection. Inverse Probl., Bd. 33 (7), S. ARTN 074001.
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Hrushikesh N. Mhaskar, Sergei V. Pereverzyev and Maria D. van der Walt (2017) A Deep Learning Approach to Diabetic Blood Glucose Prediction. Frontiers in Applied Mathematics and Statistics, S. 18.
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Hrushikesh Mhaskar, Sergei Pereverzyev and Maria D. Van Der Walt (online: 2017) A deep learning approach to diabetic blood glucose prediction. Frontiers in Applied Mathematics and Statistics, S. 18 <'http://journal.frontiersin.org/article/10.3389/fams.2017.00014/abstract'>.
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Tkachenko, Sergei V. Pereverzyev and Pavlo (2017) Regularization by the Linear Functional Strategy with Multiple Kernels. Frontiers in Applied Mathematics and Statistics, S. 9 <'http://journal.frontiersin.org/article/10.3389/fams.2017.00001/full'>.
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Pereverzyev, Sergei V.; Mathe, Peter (2017, online: 2016) Complexity of linear ill-posed problems in Hilbert space. Journal of Complexity, Bd. 38, S. 50-67 <'http://www.sciencedirect.com/science/article/pii/S0885064X16300875'>.
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Sampath, Sivananthan; Tkachenko, Pavlo; Renard, Eric; Pereverzev, Sergei V. (2016) Glycemic Control Indices and Their Aggregation in the Prediction of Nocturnal Hypoglycemia From Intermittent Blood Glucose Measurements. Journal of Diabetes Science and Technology, Bd. 10, S. 1245-1250 <'http://dst.sagepub.com/content/10/6/1245.abstract'>.
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Tkachenko, Pavlo; Kriukova, Galyna; Aleksandrova, Marharyta; Chertov, Oleg; Renard, Eric et al. [..] (2016) Prediction of nocturnal hypoglycemia by an aggregation of previously known prediction approaches: proof of concept for clinical application. Computer Methods and Programs in Biomedicine, Bd. 134, S. 179-186 <'http://www.cmpbjournal.com/article/S0169-2607(16)30164-X/abstract'>.
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Kriukova, Galyna; Pereverzyev, Sergei; Tkachenko, Pavlo (2016, online: 2015) On the convergence rate and some applications of regularized ranking algorithms. Journal of Complexity, Bd. 33, S. 14-29.
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Cao, Hui; Pereverzyev, Sergei V; Sloan, Ian H; Tkachenko, Pavlo (2016, online: 2015) Two-parameter regularization of ill-posed spherical pseudo-differential equations in the space of continuous functions. Applied Mathematics and Computation, Bd. 273, S. 993-1005.
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Kriukova, Galyna; Panasiuk, Oleksandra; Pereverzyev, Sergei V; Tkachenko, Pavlo (2016, online: 2015) A linear functional strategy for regularized ranking. Neural networks, Bd. 73, S. 26-35.
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Pereverzyev, S. V.; Sloan, I. H.; Tkachenko, P. (2015) Parameter Choice Strategies for Least-squares Approximation of Noisy Smooth Functions on the Sphere. SIAM Journal on Numerical Analysis, Bd. 53 (2), S. 820-835.
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Pereverzyev, S. V.; Tkachenko, P. (2015) Pointwise Computation in an Ill-Posed Spherical Pseudo-Differential Equation. Computational Methods in Applied Mathematics, Bd. 15 (2), S. 213–219.
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Fornasier, Massimo; Naumova, Valeriya; Pereverzyev, Sergei (2014) Parameter choice strategies for multipenalty regularization. SIAM Journal on Numerical Analysis, Bd. 52 (4), S. 1770-1794.
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Naumova, Valeriya; Pereverzyev, Sergei V.; Tkachenko, Pavlo (2014, online: 2013) Regularized collocation for spherical harmonics gravitational field modeling. International Journal on Geomathematics, Bd. 5 (1), S. 17.
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Cao, Hui; Pereverzyev, Sergei; Sincich, Eva (2014, online: 2013) Discretized Tikhonov regularization for Robin boundaries localization. Applied Mathematics and Computation, Bd. 226, S. 374–385.
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Mhaskar, Hrushikesh; Naumova, Valeriya; Pereverzyev, Sergei (2013) Filtered Legendre expansion method for numerical differentiation at the boundary point with application to blood glucose predictions. Applied Mathematics and Computation, Bd. 224, S. 835–847.
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Naumova, Valeriya; Pereverzyev, Sergei V. (2013) Multi-penalty regularization with a component-wise penalization. Inverse Problems, Bd. 29 (7), S. 1-16.
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Lu, S.; Naumova, V.; Pereverzyev, S. V. (2013, online: 2012) Legendre polynomials as a recommended basis for numerical differentiation in the presence of stochastic white noise. Journal of Inverse and Ill-Posed Problems, Bd. 21, S. 193-216.
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Naumova, V.; Pereverzyev, S. V. (2012) Blood Glucose Predictors: an Overview on How Recent Developments Help to Unlock the Problem of Glucose Regulation. Recent Patents on Computer Science, Bd. 5 (3), S. 1-11.
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Naumova, V.; Pereverzyev, S.V.; Sampath, S. (2012, online: 2012) A meta-learning approach to the regularized learning—case study: Blood glucose prediction. Neural Networks, Bd. 33, S. 181-193.
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Naumova, V.; Pereverzyev, S. V.; Sampath, S. (2012) Adaptive parameter choice for one-sided finite difference schemes and its application in diabetes technology. Journal of Complexity, Bd. 28, S. 524-538.
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Pereverzyev, Sergei V.; Solodky, Sergei G.; Volynets, Evgeny A. (2012, online: 2011) The balancing principle in solving semi-discrete inverse problems in Sobolev scales by Tikhonov method. Applicable Analysis, Bd. 91 (3), S. 435-446.
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Sivananthan, Sampath; Naumova, Valeriya; Man, Chiara Dalla; Facchinetti, Andrea; Renard, Eric et al. [..] (2011) Assessment of Blood Glucose Predictors: The Prediction-Error Grid Analysis. Diabetes Technology & Therapeutics, Bd. 13 (8), S. 787-796.
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Naumova, Valeriya; Pereverzyev, Sergei; Sampath, Sivananthan (2011) Extrapolation in variable RKHSs with application to the blood glucose reading. Inverse Problems, Bd. 27 (7), S. 13.
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Lu, Shuai; Pereverzev, Sergei V. (2011) Multi-parameter regularization and its numerical realization. Numerische Mathematik, Bd. 118 (1), S. 1-31.
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(2010) On the generalized discrepancy principle for Tikhonov regularization in Hilbert scales. Journal of Integral Equations and Applications, Bd. 22 (3), S. 483-517.
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E. De Vito, S.V. Pereverzyev and L. Rosasco (2010) Adaptive Kernel Methods Using the Balancing Principle. Foundations of Computational Mathematics, Bd. 10 (4), S. 455-479.
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Hofmann, Sergei V. Pererverzyev; Bernd (2010) Estimation of linear functionals from indirect noisy data without knowledge of the noise level. International Journal on Geomathematics, Bd. 1 (1), S. 121-131.
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Yi Heng, Shuai Lu, Adel Mhamdi and Sergei V Pereverzyev (2010) Model functions in the modified L-curve method—case study: the heat flux reconstruction in pool boiling. Inverse Problems, Bd. 26 (5), S. 13pp.
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Shuai Lu, Sergei V. Pereverzyev, and Ulrich Tautenhahn (2009) Regularized Total Least Squares: Computational Aspects and Error Bounds. SIAM Journal on Matrix Analysis and Applications, Bd. 31 (3), S. 918-941.
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Pereverzyev, Shuai Lu and Sergei V (2009) Sparse recovery by the standard Tikhonov method. Numerische Mathematik, Bd. 112 (3), S. 403-424.
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Mathe, Peter; Pereverzyev, Sergei V. (2009) The use of higher order finite difference schemes is not dangerous. Journal of Complexity, Bd. 25 (1), S. 3-10.
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Hui, Cao; Michael, Klibanov; Sergei, Pereverzyev (2009) A Carleman estimate and the balancing principle in the quasi-reversibility method for solving the Cauchy problem for the Laplace equation. Inverse problems, Bd. 25, S. 035005 (21pp).
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S. Lu, S. Pereverzyev, R. Ramlau (2007) An analysis of Tikhonov regularization for nonlinear ill-posed problems under general smoothness assumptions. Inverse Problems (23), S. 217-230.
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B. Hofmann, P. Math´e, and S. V. Pereverzyev (2007) Regularization by projection: Approximation theoretic aspects and distance functions. J. Inv. Ill-Posed Problems, Bd. 15, S. 527-545.
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B. Hofmann, P. Math´e, and S. V. Pereverzyev (2007) Regularization by projection: Approximation theoretic aspects and distance functions. J. Inv. Ill-Posed Problems, Bd. 15, S. 527–545.
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Hui Cao, Sergei V. Pereverzyev (2007) The balancing principle for the regularization of elliptic Cauchy problems. Inverse Problems, Bd. 23, S. 1943-1961.
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Lazarov, R.D.; Lu, S.; Pereverzyev, S. (2007) On the balancing principle for some problems of Numerical Analysis. Numerische Mathematik, Bd. 106, S. 659-689.
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F. Bauer, P. Mathe, S. Pereverzyev (2007) Local solutions to Inverse Problems in Geodesy. Journal of Geodesy, Bd. 81.
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Hui Cao, Sergei V. Pereverzyev (2006) Natural linearization for the identification of a diffusion coefficient in a quasi-linear parabolic system from short-time observations. Inverse Problems, Bd. 22(6), S. 2311-2330.
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P. Mathe, S. Pereverzyev (2006) Regularization of some linear ill-posed problems with discretized random noisy data. Mathematics of Computations, Bd. 75, S. 1913-1929.
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F. Bauer, S. Pereverzyev (2006) An utilization of a rough approximation of a noise covariance within the framework of multi-parameter regularization. International Journal of Tomography and Statistics, Bd. 4, S. 1-12.
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S. Lu, S. Pereverzyev (2006) Numerical differentiation from a view point of Regularization Theory. Mathematics of Computations, Bd. 75, S. 1853-1870.
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P. Mathe, S. Pereverzyev (2006) The discretized discrepancy principle under general source conditions. Journal of Complexity, Bd. 22, S. 371-381.
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Nair, T.; Pereverzyev, S.; Tauthenhahn, U. (2005) Regularization in Hilbert scales under general smoothing conditions. Inverse Problems, Bd. 21(6), S. 1851-1871.
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Bauer, F.; Pereverzyev, S. (2005) Regularization without preliminary knowledge of smoothness and error behaviour. European Journal of Applied Mathematics, Bd. 16(3), S. 303-317.
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Engl, H.; Fusek, P.; Pereverzyev, S. (2005) Natural linearization for the identification of nonlinear heat transfer laws. Journal of Inverse and Ill-posed Problems, Bd. 13(6), S. 567-582.
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Pereverzyev, S.; Schock, E. (2005) On the adaptive selection of the parameter in regularization of ill-posed problems. SIAM J. Numer. Analysis, Bd. 43(5), S. 2060-2076.
Book/Monograph (6)
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Pereverzyev, Sergei (2022) An Introduction to Artificial Intelligence Based on Reproducing Kernel Hilbert Spaces. In Reihe: Compact Textbooks in Mathematics: Birkhäuser Cham.
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H.N. Mhaskar, S.V. Pereverzyev, V.Yu. Semenov, E.V. Semenova (2020) Data Based Construction of Kernels for Classification. In Reihe: MATRIX Book Series 3, hrsg. v. al., J. de Gier et; Basel, Switzerland: Springer Nature Switzerland AG.
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Mykola Krasnoschok, Sergei Pereverzyev, Sergii V. Siryk, Nataliya Vasylyeva (2020) Regularized Reconstruction of the Order in Semilinear Subdiffusion with Memory. In Reihe: Springer Proceedings in Mathematics & Statistics, hrsg. v. Cheng J., Lu S., Yamamoto M.; Singapore: Springer.
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Naumova, Valeriya; Nita, Lucian; Poulsen, Jens Ulrik; Pereverzyev, Sergei V. (2016) Meta-Learning Based Blood Glucose Predictor for Diabetic Smartphone App. In Reihe: Lecture Notes in Bioengineering, hrsg. v. Kirchsteiger, Harald; Jørgensen, John Bagterp; Renard, Eric; Re, Luigi del, 1. Aufl.: Springer International Publishing.
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Pereverzyev, Sergiy V.; Lu, Shuai (2013) Regularization Theory for Ill-Posed Problems. Selected Topics. In Reihe: Inverse and Ill-Posed Problems Series, hrsg. v. Kabanikhin, Sergei; Berlin, Boston: DeGruyter (287 Seiten).
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Sergei Pereverzyev, Shuai Lu (2010) Multiparameter Regularization in Downward Continuation of Satellite Data., hrsg. v. Willi Freeden, M. Zuhair Nashed, Thomas Sonar; Berlin: Springer (21 Seiten).
Conference Contribution: Publication in Proceedings (8)
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Marius-Constantin Dinu, Markus Holzleitner, Maximilian Beck, Hoan Duc Nguyen, Andrea Huber, Hamid Eghbal-zadeh, Bernhard A. Moser, Sergei Pereverzyev, Sepp Hochreiter, Werner Zellinger (2023) Addressing Parameter Choice Issues in Unsupervised Domain Adaptation by Aggregation. (ICLR 2023, The Eleventh International Conference on Learning Representations).
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Werner Zellinger, Natalia Shepeleva, Marius-Constantin Dinu, Hamid Eghbal-zadeh, Hoan Duc Nguyen, Bernhard Nessler, Sergei Pereverzyev, Bernhard A. Moser (2021) The balancing principle for parameter choice in distance-regularized domain adaptation. (NeurIPS 2021, Thirty-fifth Conference on Neural Information Processing Systems).
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Naumova, Valeriya; Pereverzyev, Sergei V.; Sampath, Sivananthan (2011) Reading Blood Glucose from Subcutaneous Electric Current by Means of a Regularization in Variable Reproducing Kernel Hilbert Spaces. (50th IEEE Conference on Decision and Control and European Control Conference), S. 5158-5163.
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Pereverzyev, Sergei; Sampath, Sivananthan (2009) Regularized Learning Algorithm for Prediction of Blood Glucose Concentration in ``No Action Period''. In: Perumal Nithiarasu, Rainald Löhner and Raoul van Loon (Hrsg.), 1st International Conference on Computational & Mathematical Biomedical Engineering (1st International Conference on Computational & Mathematical Biomedical Engineering) In Reihe: CMBE09; Linz: CMBE, S. 395-398.
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Hui, Cao; Sergei, Pereverzyev; Eva, Sincich (2008) Natural liearization for corrosion identification., ICIPE proceedings In Reihe: ICIPE proceedings: IOP.
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Shuai Lu, Sergei V. Pereverzyev (2008) Sparsity reconstruction by means of the standard Tikhonov regularization. In: Bonnet, Marc (Hrsg.) (6TH INTERNATIONAL CONFERENCE ON INVERSE PROBLEMS IN ENGINEERING: THEORY AND PRACTICE); Paris: IOP Publishing Limited, S. 012066.
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S. Lu, S.V.Pereveryzev (2008) Sparsity reconstruction by means of the standard Tikhonov regularization. (6th International Conference on Inverse Problems in Engineering: Theory and Practice ICIPE (Dourdan, 15.06.2008)).
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Galyna Kriukova, Nadiya Shvai, Sergei V. Pereverzyev Application of Regularized Ranking and Collaborative Filtering in Predictive Alarm Algorithm for Nocturnal Hypoglycemia Prevention. (The 9th International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications); Romania.
Conference Contribution: Poster (in Proceedings) (2)
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Naumova, Valeriya; Pereverzyev, Sergei V. (2013) Data-Driven and Problem-Oriented Multiple-Kernel Learning (Poster). International Workshop on advances in Regulariza- tion, Optimization, Kernel Methods and Support Vector Machines: theory and applications.
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S. Sivananthan, V. Naumova, C. Dalla Man, A. Facchinetti, E. Renard, C. Cobelli, S. V. Pereverzev (2011) Assessment of blood glucose predictors: the Prediction-Error Grid Analysis (PRED-EGA) (Poster). The 4th International Conference on Advanced Technologies & Treatments in Diabetes.
Contribution in Collection (3)
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Sergei V. Pereverzyev, Evgeniya V. Semenova and Pavlo Tkachenko (2019) Regularized Quadrature Methods for Fredholm Integral Equations of the First Kind. In: Josef Dick, Frances Y. Kuo, Henryk Wozniakowski (Hrsg.), Contemporary Computational Mathematics - A Celebration of the 80th Birthday of Ian Sloan: Springer.
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Sergei V. Pereverzyev, Evgeniya Semenova and Pavlo Tkachenko (2018) Regularized Quadrature Methods for Fredholm Integral Equations of the First Kind. In: Josef Dick, Frances Y. Kuo, Henryk Wozniakowski (Hrsg.), Contemporary Computational Mathematics - A Celebration of the 80th Birthday of Ian Sloan: Springer.
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Pereverzyev, Hui Cao and Sergei (2010) Regularization of naturally linearized parameter identification problems and the application of the balancing principle. In: Yanfei Wang, Anatoly G. Yagola and Changchun Yang (Hrsg.), Optimization and regularization for computational inverse problems and applications: Springer, S. 65-106.
Editorship (2)
Research Report (23)
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Nguyen, Duc Hoan; Zellinger, Werner; Pereverzyev, Sergei V. (2023) On regularized Radon-Nikodym differentiation. Bericht-Nr. 2023-13; RICAM:.
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Kriukova, Galyna; Panasiuk, Oleksandra; Pereverzyev, Sergei V.; Tkachenko, Pavlo (2015) A Linear Functional Strategy for Regularized Ranking. Bericht-Nr. 2015-13; RICAM: Linz.
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Kriukova, Galyna; Pereverzyev, Sergei V.; Tkachenko, Pavlo (2014) On the convergence rate and some applications of regularized ranking algorithms. Bericht-Nr. 2014-21; RICAM: Linz.
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Cao, Hui; Pereverzyev, Sergei; Sloan, Ian H.; Tkachenko, Pavlo (2014) Two-parameter regularization of ill-posed spherical pseudo-differential equations in the space of continuous functions. Bericht-Nr. 2014-17; RICAM: Linz.
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Pereverzyev, Sergiy V.; Tkachenko, Pavlo (2014) Approximation of the solution of an ill-posed spherical pseudo-differential equation at a given point. RICAM: Linz.
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Pereverzyev, Sergei V.; Sloan, Ian H.; Tkachenko, Pavlo (2014) Parameter choice strategies for least-squares approximation of noisy smooth functions on the sphere. Bericht-Nr. 2014-04; RICAM: Linz.
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Naumova, Valeriya; Pereverzyev, Sergei V.; Tkachenko, Pavlo (2013, online: 2013) Regularized collocation for Spherical harmonics Gravitational Field Modeling. Bericht-Nr. 2013-12; RICAM: Linz.
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Fornasier, Massimo; Naumova, Valeriya; Pereverzyev, Sergei (2013) Parameter Choice Strategies for Multi-Penalty Regularization. Bericht-Nr. RICAM Report No 2013-10; RICAM: Linz.
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Mhaskar, Hrushikesh; Naumova, Valeriya; Pereverzyev, Sergei V. (2013) Filtered Legendre Expansion Method for Numerical Differentiation at the Boundary Point with Application to Blood Glucose Predictions. Bericht-Nr. 2013-07; RICAM: Linz.
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Naumova, Valeriya; Pereverzyev, Sergei (2013) Multi-Penalty Regularization with a Component-Wise Penalization. Bericht-Nr. 2013-03; RICAM: Linz.
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Keller, Alexander; Kuo, Frances; Neuenkirch, Andreas; Traub, Joseph F. (2013) Algorithms and Complexity for Continuous Problems (Dagstuhl Seminar 12391). Bericht-Nr. 2(9) 2013; Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik: Dagstuhl, Germany.
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Naumova, V.; Pereverzyev, S.; Sampath, S. (2012) A Meta-Learning Approach to the Adaptive Regularization – Case Study: Blood Glucose Prediction. Bericht-Nr. 51/2012; Mathematisches Forschungsinstitut Oberwolfach: Oberwolfach.
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Naumova, V.; Pereverzyev, S.; Sampath, S. (2012) Regularization in Variable RKHSs with application to the Blood Glucose Reading. Bericht-Nr. 51/2012; Mathematisches Forschungsinstitut Oberwolfach: Oberwolfach.
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Pereverzyev, S. V.; Naumova, V.; Sampath, S. (2012) Learning in Variable RKHSs with application to the Blood Glucose Reading. Bericht-Nr. 31/2012; Oberwolfach.
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Lu, S.; Naumova, V.; Pereverzyev, S.V. (2012) Numerical differentiation by means of Legendre polynomials in the presence of square summable noise. Bericht-Nr. 2012-15; Linz.
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Naumova, V.; Pereverzyev, S.; Sampath, S. (2011, online: 2012) A Meta-Learning Approach to the Regularized Learning -- Case Study: Blood Glucose Prediction. Bericht-Nr. 2011-31; Linz.
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Naumova, Valeriya; Pereverzyev, Sergei; Sampath, Sivananthan (2011) Adaptive parameter choice for one-sided finite difference schemes and its application in diabetes technology. Bericht-Nr. 2011-18;.
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Naumova, Valeriya; Pereverzev, Sergei; Sampath, Sivananthan (2011) Extrapolation in variable RKHSs with application to the BG reading. Bericht-Nr. 2011-04; RICAM:.
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Lu, Shuai; Pereverzyev, Sergei V; Shao, Yuanyuan; Tautenhahn, Ulrich (2010) On the generalized discrepancy principle for Tikhonov regularization in Hilbert scales. Bericht-Nr. 2009-19;.
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Heng, Yi; Lu, Shuai; Mhamdi, Adel; Pereverzyev, Sergei V. (2009) Model function approach in the modified L-curve method for the choice of regularization parameter. Bericht-Nr. 2009-08;.
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Lu, Shuai; Pereverzyev, Sergei V (2009) Multi-parameter regularization and its numerical realization. Bericht-Nr. 2009-11;.
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Shuai Lu, Sergei V. Pereverzyev (2008) Sparsity reconstruction by the standard Tikhonov method. Bericht-Nr. 2008-17;.
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Shuai Lu, Sergei V. Pereverzyev, Ulrich Tautenhahn (2008) A model function method in total least squares. Bericht-Nr. 2008-18;.