Sergei Pereverzyev

Prof. Dr.

Sergei Pereverzyev

Prof. Dr.

Senior Research Scientist
Inverse Problems and Mathematical Imaging

+43 732 2468 5215
Sergei.Pereverzyev(at)ricam.oeaw.ac.at

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

Regularized Reconstruction of Scalar Parameters in Subdiffusion with Memory via a Nonlocal Observation. / Pereverzyev, Sergiy; Hulianytskyi, Andrii ; Siryk, Sergii et al.
in: Applied Mathematics and Optimization, Jahrgang 93, 67, 06.04.2026.
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Multiparameter regularization and aggregation in the context of polynomial functional regression. / Pereverzyev, Sergiy; Gizewski, Elke R. ; Holzleitner, Markus et al.
in: Analysis and Applications, 23.10.2025.
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Identification of the Memory Order in Multi-Term Semilinear Subdiffusion. / Pereverzyev, Sergei; Sergii, V; Siryk, and Nataliya Vasylyeva.
in: Numerical Functional Analysis and Optimization, Jahrgang 46, 06.01.2025, S. 1 -35.
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Quasi-optimality approach in the reconstruction of singularities in multi-term subdiffusion equations. / Pereverzyev, Sergiy; Vasylyeva, Nataliya ; Hulianytskyi, Andrii .
in: Electr. Trans. Num. Anal. (ETNA), Jahrgang 64, 2025, S. 45-79.
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General regularization scheme in data-driven learning of Koopman operators. / Pereverzyev, S; Solodky, S.
in: JOURNAL OF APPLIED AND NUMERICAL ANALYSIS, Jahrgang 2, 17.12.2024, S. 77 - 84.
DOI RIS ENW BIB
On Regularized Radon–Nikodym Differentiation. / Nguyen, Duc Hoan; Zellinger, Werner; Pereverzyev, Sergei.
in: Journal of Machine Learning Research, Jahrgang 25, 15.10.2024, S. 1-24.
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On regularized polynomial functional regression. / Holzleitner, Markus; Sergei, V.
in: Journal of Complexity, Jahrgang 83, 01.08.2024, S. 25.
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Advancing electrochemical impedance analysis through innovations in the distribution of relaxation times method. / Maradesa, Adeleke; Pereverzyev, Sergei; Zic, Mark et al.
in: Joule, Jahrgang 8, 07.06.2024, S. 1-24.
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Domain Generalization by Functional Regression. / Holzleitner, Markus; Pereverzyev, Sergei V; Zellinger, Werner.
in: Numerical Functional Analysis and Optimization, Jahrgang 45, Nr. 3, 17.05.2024, S. 259-281.
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Adaptive learning of density ratios in RKHS. / Zellinger, Werner; Kindermann, Stefan; Sergei, Pereverzyev.
in: Journal of Machine Learning Research, Jahrgang 24, Nr. 1004, 30.12.2023, S. 1-28.
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Two-layer networks with the (text {ReLU}^k) activation function: Barron spaces and derivative approximation. / Li, Yuanyuan; Lu, Shuai; Mathé, Peter et al.
in: Numerische Mathematik, Jahrgang 155, 23.11.2023, S. 1-25.
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Application of self-adapting regularization, machine learning tools and limits in Levenberg-Marquardt algorithm to solve CNLS problem. / Žic, Mark; Pereverzyev, Sergiy.
in: JOURNAL OF ELECTROANALYTICAL CHEMISTRY, Jahrgang 939, 15.06.2023, S. 117420.
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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. / M, Kunaver and Z; Rojec, and V; Subotic, and S et al.
in: Journal of the Electrochemical Society, Jahrgang 169, Nr. 11, 16.11.2022, S. 110529.
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On a regularization of unsupervised domain adaptation in RKHS. / Elke, R; Gizewski, Lukas Mayer; Bernhard, A et al.
in: Applied and Computational Harmonic Analysis, Jahrgang 57, 01.03.2022, S. 201-227.
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Extraction of Distribution Function of Relaxation Times by using Levenberg-Marquardt Algorithm: A New Approach to Apply a Discretization Error Free Jacobian Matrix. / Zic, M; Vlasic, L; Subotic, V et al.
in: Journal of the Electrochemical Society, Jahrgang 169, Nr. 3, 01.03.2022, S. ARTN 030508.
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A Function Approximation Approach to the Prediction of Blood Glucose Levels. / Mhaskar, Hrushikesh; Pereverzyev, Sergei; Walt, Maria Dorothea Van Der.
in: Frontiers in Applied Mathematics and Statistics, Jahrgang 7, 31.08.2021, S. 13.
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A function approximation approach to the prediction of blood glucose levels. / Mhaskar, H N; S, V Pereverzyev and M; Walt, D Van Der.
in: Frontiers in Applied Mathematics and Statistics, Jahrgang 11, 10.08.2021, S. 10.
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Investigation of Electrochemical Processes in Solid Oxide Fuel Cells by Modified Levenberg-Marquardt Algorithm: A New Automatic Update Limit Strategy. / Zic, Mark; Fajfar, Iztok; Subotic, Vanja et al.
in: Processes, Jahrgang 9, Nr. 1, 15.01.2021, S. ARTN 108.
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Randomized matrix approximation to enhance regularized projection schemes in inverse problems. / Lu, Shuai; Mathe, Peter; Pereverzyev, Sergei.
in: Inverse Problems, Jahrgang 36, 20.08.2020, S. 20.
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Randomized matrix approximation to enhance regularized projection schemes in inverse problems. / Lu, Shuai; Peter, Mathé and Sergei V; Pereverzyev, Sergiy.
in: Inverse Problems, Jahrgang 36, Nr. 8, 20.08.2020, S. 085013 (20pp).
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Determination of the fractional order in semilinear subdiffusion equations. / Krasnoschok, M; Pereverzyev, S; Siryk, S.V et al.
in: Fractional Calculus and Applied Analysis, Jahrgang 23, Nr. 3, 01.07.2020, S. 694 - 722.
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Solving CNLS problems using Levenberg-Marquardt algorithm: A new fitting strategy combining limits and a symbolic Jacobian matrix. / Žic, Mark; Subotic, Vanja; Pereverzev, Sergei V et al.
in: JOURNAL OF ELECTROANALYTICAL CHEMISTRY, Jahrgang 866, Nr. 1, 08.05.2020, S. 114171.
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Solving CNLS problems using Levenberg-Marquardt algorithm: A new fitting strategy combining limits and a symbolic Jacobian matrix. / Žica, Mark; Subotićb, Vanja; Pereverzyev, Sergei et al.
in: JOURNAL OF ELECTROANALYTICAL CHEMISTRY, Jahrgang 866, Nr. 1, 08.05.2020, S. 114171.
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Adaptive multi-parameter regularization approach to construct the distribution function of relaxation times. / Žic, Mark; Jr, Sergiy Pereverzyev; Subotić, Vanja et al.
in: International Journal on Geomathematics, Jahrgang 11, Nr. 2, 15.01.2020, S. 1-23.
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Regularized Collocation in Distribution of Diffusion Times Applied to Electrochemical Impedance Spectroscopy. / Pereverzyev, S.V; Solodky, S.G; Vasylyk, V.B et al.
in: Computational Methods in Applied Mathematics, Jahrgang 20, 11.11.2019, S. 8.
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Optimizing noisy CNLS problems by using Nelder-Mead algorithm: A new method to compute simplex step efficiency. / Žic, Mark; Pereverzyev, Sergei.
in: JOURNAL OF ELECTROANALYTICAL CHEMISTRY, Jahrgang 851, 10.10.2019, S. 113439.
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Data Based Construction of Kernels for Semi-supervised Learning with Less Labels. / Mhaskar, Hrushikesh; Pereverzyev, Sergei; Semenova, Vasyl Semenov and Evgeniya.
in: Frontiers in Applied Mathematics and Statistics, Jahrgang 4, 11.04.2019, S. 12.
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Balancing principle in supervised learning for a general regularization scheme. / Sergei, V; Pereverzyev, Shuai Lu; Mathé, Peter.
in: Applied and Computational Harmonic Analysis, Jahrgang 45, 21.03.2018, S. 26.
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Nystrom type subsampling analyzed as a regularized projection. / Kriukova, Galyna; Pereverzyev, Sergiy; Tkachenko, Pavlo et al.
in: Inverse Problems, Jahrgang 33, Nr. 7, 15.07.2017, S. ARTN 074001.
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A Deep Learning Approach to Diabetic Blood Glucose Prediction. / Hrushikesh, N; Mhaskar, Sergei V; Pereverzyev, and Maria D et al.
in: Frontiers in Applied Mathematics and Statistics, 14.07.2017, S. 18.
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A deep learning approach to diabetic blood glucose prediction. / Mhaskar, Hrushikesh; Sergei, Pereverzyev and Maria D; Walt, Van Der.
in: Frontiers in Applied Mathematics and Statistics, 28.06.2017, S. 18.
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Regularization by the Linear Functional Strategy with Multiple Kernels. / Sergei, V; Tkachenko, Pereverzyev and Pavlo.
in: Frontiers in Applied Mathematics and Statistics, 03.02.2017, S. 9.
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Complexity of linear ill-posed problems in Hilbert space. / Sergei, V; Mathe, Peter.
in: Journal of Complexity, Jahrgang 38, 10.01.2017, S. 50-67.
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Glycemic Control Indices and Their Aggregation in the Prediction of Nocturnal Hypoglycemia From Intermittent Blood Glucose Measurements. / Sampath, Sivananthan; Tkachenko, Pavlo; Renard, Eric et al.
in: Journal of Diabetes Science and Technology, Jahrgang 10, 02.11.2016, S. 1245-1250.
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Prediction of nocturnal hypoglycemia by an aggregation of previously known prediction approaches: proof of concept for clinical application. / Tkachenko, Pavlo; Kriukova, Galyna; Aleksandrova, Marharyta et al.
in: Computer Methods and Programs in Biomedicine, Jahrgang 134, 08.07.2016, S. 179-186.
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On the convergence rate and some applications of regularized ranking algorithms. / Kriukova, Galyna; Pereverzyev, Sergei; Tkachenko, Pavlo.
in: Journal of Complexity, Jahrgang 33, 02.02.2016, S. 14-29.
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A linear functional strategy for regularized ranking. / Kriukova, Galyna; Panasiuk, Oleksandra; Pereverzyev, Sergei V et al.
in: Neural Networks, Jahrgang 73, 15.01.2016, S. 26-35.
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Two-parameter regularization of ill-posed spherical pseudo-differential equations in the space of continuous functions. / Cao, Hui; Pereverzyev, Sergei V; Sloan, Ian H et al.
in: Applied Mathematics and Computation, Jahrgang 273, 15.01.2016, S. 993-1005.
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Parameter Choice Strategies for Least-squares Approximation of Noisy Smooth Functions on the Sphere. / Pereverzyev, S V; Sloan, I H; Tkachenko, P.
in: SIAM Journal on Numerical Analysis, Jahrgang 53, Nr. 2, 24.03.2015, S. 820-835.
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Pointwise Computation in an Ill-Posed Spherical Pseudo-Differential Equation. / Pereverzyev, S V; Tkachenko, P.
in: Computational Methods in Applied Mathematics, Jahrgang 15, Nr. 2, 11.03.2015, S. 213–219.
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Parameter choice strategies for multipenalty regularization. / Fornasier, Massimo; Naumova, Valeriya; Pereverzyev, Sergei.
in: SIAM Journal on Numerical Analysis, Jahrgang 52, Nr. 4, 31.07.2014, S. 1770-1794.
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Regularized collocation for spherical harmonics gravitational field modeling. / Naumova, Valeriya; Sergei, V; Tkachenko, Pavlo.
in: International Journal on Geomathematics, Jahrgang 5, Nr. 1, 20.04.2014, S. 17.
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Discretized Tikhonov regularization for Robin boundaries localization. / Cao, Hui; Pereverzyev, Sergei; Sincich, Eva.
in: Applied Mathematics and Computation, Jahrgang 226, 01.01.2014, S. 374–385.
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Filtered Legendre expansion method for numerical differentiation at the boundary point with application to blood glucose predictions. / Mhaskar, Hrushikesh; Naumova, Valeriya; Pereverzyev, Sergei.
in: Applied Mathematics and Computation, Jahrgang 224, 16.10.2013, S. 835–847.
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Multi-penalty regularization with a component-wise penalization. / Naumova, Valeriya; Sergei, V.
in: Inverse Problems, Jahrgang 29, Nr. 7, 10.06.2013, S. 1-16.
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Legendre polynomials as a recommended basis for numerical differentiation in the presence of stochastic white noise. / Lu, S; Naumova, V; Pereverzyev, S V.
in: Journal of Inverse and Ill-Posed Problems, Jahrgang 21, 14.02.2013, S. 193-216.
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Blood Glucose Predictors: an Overview on How Recent Developments Help to Unlock the Problem of Glucose Regulation. / Naumova, V; Pereverzyev, S V.
in: Recent Advances in Computer Science and Communications, Jahrgang 5, Nr. 3, 05.12.2012, S. 1-11.
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A meta-learning approach to the regularized learning—case study: Blood glucose prediction. / Naumova, V; Pereverzyev, S.V; Sampath, S.
in: Neural Networks, Jahrgang 33, 02.10.2012, S. 181-193.
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Adaptive parameter choice for one-sided finite difference schemes and its application in diabetes technology. / Naumova, V; Pereverzyev, S V; Sampath, S.
in: Journal of Complexity, Jahrgang 28, 10.09.2012, S. 524-538.
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The balancing principle in solving semi-discrete inverse problems in Sobolev scales by Tikhonov method. / Sergei, V; Sergei, G; Evgeny, A.
in: Applicable Analysis, Jahrgang 91, Nr. 3, 01.03.2012, S. 435-446.
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Assessment of Blood Glucose Predictors: The Prediction-Error Grid Analysis. / Sivananthan, Sampath; Naumova, Valeriya; Man, Chiara Dalla et al.
in: Diabetes Technology and Therapeutics, Jahrgang 13, Nr. 8, 01.08.2011, S. 787-796.
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Extrapolation in variable RKHSs with application to the blood glucose reading. / Naumova, Valeriya; Pereverzyev, Sergei; Sampath, Sivananthan.
in: Inverse Problems, Jahrgang 27, Nr. 7, 14.06.2011, S. 13.
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Multi-parameter regularization and its numerical realization. / Lu, Shuai; Sergei, V.
in: Numerische Mathematik, Jahrgang 118, Nr. 1, 18.01.2011, S. 1-31.
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On the generalized discrepancy principle for Tikhonov regularization in Hilbert scales. / Lu, Shuai; Pereverzyev, Sergiy.
in: Journal of Integral Equations and Applications, Jahrgang 22, Nr. 3, 12.09.2010, S. 483-517.
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Adaptive Kernel Methods Using the Balancing Principle. / Vito, E De; Pereverzyev, S.V; and, L.
in: Foundations of Computational Mathematics, Jahrgang 10, Nr. 4, 28.06.2010, S. 455-479.
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Estimation of linear functionals from indirect noisy data without knowledge of the noise level. / Sergei, V; Hofmann, Bernd.
in: International Journal on Geomathematics, Jahrgang 1, Nr. 1, 22.06.2010, S. 121-131.
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Model functions in the modified L-curve method—case study: the heat flux reconstruction in pool boiling. / Heng, Yi; Lu, Shuai; Pereverzyev, Adel Mhamdi and Sergei V.
in: Inverse Problems, Jahrgang 26, Nr. 5, 15.04.2010, S. 13pp.
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Regularized Total Least Squares: Computational Aspects and Error Bounds. / Lu, Shuai; Sergei, V; Pereverzyev, and Ulrich Tautenhahn.
in: SIAM Journal on Matrix Analysis and Applications, Jahrgang 31, Nr. 3, 05.08.2009, S. 918-941.
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Sparse recovery by the standard Tikhonov method. / Pereverzyev, Shuai Lu and Sergei V; Lu, Shuai.
in: Numerische Mathematik, Jahrgang 112, Nr. 3, 02.05.2009, S. 403-424.
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The use of higher order finite difference schemes is not dangerous. / Mathe, Peter; Pereverzyev, Sergei V.
in: Journal of Complexity, Jahrgang 25, Nr. 1, 21.01.2009, S. 3-10.
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A Carleman estimate and the balancing principle in the quasi-reversibility method for solving the Cauchy problem for the Laplace equation. / Hui, Cao; Michael, Klibanov; Sergei, Pereverzyev.
in: Inverse Problems, Jahrgang 25, 15.01.2009, S. 035005 (21pp).
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An analysis of Tikhonov regularization for nonlinear ill-posed problems under general smoothness assumptions. / Lu, S; Pereverzyev, S; Ramlau, R.
in: Inverse Problems, Nr. 23, 11.12.2007, S. 217-230.
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Regularization by projection: Approximation theoretic aspects and distance functions. / Hofmann, B; Math, P; e, and S et al.
in: Journal of Inverse and Ill-Posed Problems, Jahrgang 15, 07.12.2007, S. 527-545.
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Regularization by projection: Approximation theoretic aspects and distance functions. / Hofmann, B; Math, P; e, and S et al.
in: J. Inv. Ill-Posed Problems, Jahrgang 15, 15.10.2007, S. 527–545.
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The balancing principle for the regularization of elliptic Cauchy problems. / Cao, Hui; Sergei, V.
in: Inverse Problems, Jahrgang 23, 24.08.2007, S. 1943-1961.
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On the balancing principle for some problems of Numerical Analysis. / Lazarov, R.D; Lu, S; Pereverzyev, S.
in: Numerische Mathematik, Jahrgang 106, 24.04.2007, S. 659-689.
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Local solutions to Inverse Problems in Geodesy. / Bauer, F; Mathe, P; Pereverzyev, S.
in: Journal of Geodesy, Jahrgang 81, 10.04.2007.
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Natural linearization for the identification of a diffusion coefficient in a quasi-linear parabolic system from short-time observations. / Cao, Hui; Sergei, V.
in: Inverse Problems, Jahrgang 22(6), 22.11.2006, S. 2311-2330.
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An utilization of a rough approximation of a noise covariance within the framework of multi-parameter regularization. / Bauer, F; Pereverzyev, S.
in: International Journal of Tomography and Statistics, Jahrgang 4, 15.06.2006, S. 1-12.
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Regularization of some linear ill-posed problems with discretized random noisy data. / Mathe, P; Pereverzyev, S.
in: Mathematics of Computation, Jahrgang 75, 15.06.2006, S. 1913-1929.
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Numerical differentiation from a view point of Regularization Theory. / Lu, S; Pereverzyev, S.
in: Mathematics of Computation, Jahrgang 75, 15.05.2006, S. 1853-1870.
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The discretized discrepancy principle under general source conditions. / Mathe, P; Pereverzyev, S.
in: Journal of Complexity, Jahrgang 22, 07.03.2006, S. 371-381.
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Natural linearization for the identification of nonlinear heat transfer laws. / Engl, H; Fusek, P; Pereverzyev, S.
in: Journal of Inverse and Ill Posed Problems, Jahrgang 13(6), 15.06.2005, S. 567-582.
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Regularization without preliminary knowledge of smoothness and error behaviour. / Bauer, F; Pereverzyev, S.
in: European Journal of Applied Mathematics, Jahrgang 16(3), 15.06.2005, S. 303-317.
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Regularization in Hilbert scales under general smoothing conditions. / Nair, T; Pereverzyev, S; Tauthenhahn, U.
in: Inverse Problems, Jahrgang 21(6), 15.06.2005, S. 1851-1871.
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On the adaptive selection of the parameter in regularization of ill-posed problems. / Pereverzyev, S; Schock, E.
in: SIAM J. Numer. Analysis, Jahrgang 43(5), 15.06.2005, S. 2060-2076.
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Randomized matrix approximation to enhance regularized projection schemes in inverse problems. / Lu, Shuai; Pereverzyev, Peter Mathé and Sergei V.
in: Inverse Problems, Jahrgang 36, Nr. 6, 12.06.2020, S. 085013 (20pp).
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Addressing Parameter Choice Issues in Unsupervised Domain Adaptation by Aggregation. / Dinu, Marius-Constantin; Holzleitner, Markus; Beck, Maximilian et al.
ICLR 2023, The Eleventh International Conference on Learning Representations. 2023.
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The balancing principle for parameter choice in distance-regularized domain adaptation. / Zellinger, Werner; Shepeleva, Natalia; Dinu, Marius-Constantin et al.
NeurIPS 2021, Thirty-fifth Conference on Neural Information Processing Systems. 2021.
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Reading Blood Glucose from Subcutaneous Electric Current by Means of a Regularization in Variable Reproducing Kernel Hilbert Spaces. / Naumova, Valeriya; Pereverzyev, Sergei V; Sampath, Sivananthan.
50th IEEE Conference on Decision and Control and European Control Conference. 2011. S. 5158-5163.
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Regularized Learning Algorithm for Prediction of Blood Glucose Concentration in ``No Action Period''. / Pereverzyev, Sergei; Sampath, Sivananthan; Nithiarasu, Perumal (Herausgeber:in) et al.
1st International Conference on Computational & Mathematical Biomedical Engineering. Linz: CMBE, 2009. S. 395-398 (CMBE09).
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Sparsity reconstruction by means of the standard Tikhonov regularization. / Lu, Shuai; Sergei, V; Bonnet, Marc (Herausgeber:in).
6TH INTERNATIONAL CONFERENCE ON INVERSE PROBLEMS IN ENGINEERING: THEORY AND PRACTICE. Paris: IOP Publishing Limited, 2008. S. 012066.
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Natural liearization for corrosion identification. / Hui, Cao; Sergei, Pereverzyev; Eva, Sincich.
ICIPE proceedings. IOP, 2008. (ICIPE proceedings).
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Sparsity reconstruction by means of the standard Tikhonov regularization. / Lu, S; Pereverzyev, Sergiy.
6th International Conference on Inverse Problems in Engineering: Theory and Practice ICIPE (Dourdan, 15.06.2008). 2008.
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Application of Regularized Ranking and Collaborative Filtering in Predictive Alarm Algorithm for Nocturnal Hypoglycemia Prevention. / Kriukova, Galyna; Shvai, Nadiya; Sergei, V.
The 9th International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications. Romania, 2017.
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On regularized Radon-Nikodym differentiation. / Nguyen, Duc Hoan; Zellinger, Werner; Pereverzyev, Sergei V.
2023.
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A Linear Functional Strategy for Regularized Ranking. / Kriukova, Galyna; Panasiuk, Oleksandra; Sergei, V et al.
Linz, 2015. 29 S.
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On the convergence rate and some applications of regularized ranking algorithms. / Kriukova, Galyna; Sergei, V; Tkachenko, Pavlo.
Linz, 2014. 26 S.
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Two-parameter regularization of ill-posed spherical pseudo-differential equations in the space of continuous functions. / Cao, Hui; Pereverzyev, Sergei; Ian, H et al.
Linz, 2014. 19 S.
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Approximation of the solution of an ill-posed spherical pseudo-differential equation at a given point. / Sergiy, V; Tkachenko, Pavlo.
Linz, 2014. 13 S.
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Parameter choice strategies for least-squares approximation of noisy smooth functions on the sphere. / Sergei, V; Ian, H; Tkachenko, Pavlo.
Linz, 2014. 16 S.
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Regularized collocation for Spherical harmonics Gravitational Field Modeling. / Naumova, Valeriya; Sergei, V; Tkachenko, Pavlo.
Linz, 2013. 18 S.
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Parameter Choice Strategies for Multi-Penalty Regularization. / Fornasier, Massimo; Naumova, Valeriya; Pereverzyev, Sergei.
Linz, 2013. 24 S.
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Filtered Legendre Expansion Method for Numerical Differentiation at the Boundary Point with Application to Blood Glucose Predictions. / Mhaskar, Hrushikesh; Naumova, Valeriya; Pereverzyev, Sergei V.
Linz, 2013. 20 S.
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Multi-Penalty Regularization with a Component-Wise Penalization. / Naumova, Valeriya; Pereverzyev, Sergei.
Linz, 2013. 16 S.
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Algorithms and Complexity for Continuous Problems (Dagstuhl Seminar 12391). / Keller, Alexander; Kuo, Frances; Neuenkirch, Andreas et al.
Dagstuhl, Germany, 2013. 25 S.
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A Meta-Learning Approach to the Adaptive Regularization – Case Study: Blood Glucose Prediction. / Naumova, V; Pereverzyev, S; Sampath, S.
Oberwolfach, 2012. 33 S.
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Regularization in Variable RKHSs with application to the Blood Glucose Reading. / Naumova, V; Pereverzyev, S; Sampath, S.
Oberwolfach, 2012. 31 S.
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Learning in Variable RKHSs with application to the Blood Glucose Reading. / Pereverzyev, S V; Naumova, V; Sampath, S.
Oberwolfach, 2012.
DOI RIS ENW BIB
Numerical differentiation by means of Legendre polynomials in the presence of square summable noise. / Lu, S; Naumova, V; Pereverzyev, S.V.
Linz, 2012. 18 S.
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A Meta-Learning Approach to the Regularized Learning -- Case Study: Blood Glucose Prediction. / Naumova, V; Pereverzyev, S; Sampath, S.
Linz, 2011. 18 S.
Website RIS ENW BIB
Adaptive parameter choice for one-sided finite difference schemes and its application in diabetes technology. / Naumova, Valeriya; Pereverzyev, Sergei; Sampath, Sivananthan.
2011. 20 S.
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Extrapolation in variable RKHSs with application to the BG reading. / Naumova, Valeriya; Pereverzev, Sergei; Sampath, Sivananthan.
2011. 12 S.
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Sergei Pereverzyev

Sergei Pereverzyev

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