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
Identification of the Memory Order in Multi-Term Semilinear Subdiffusion
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.Advancing electrochemical impedance analysis through innovations in the distribution of relaxation times method
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.Two-layer networks with the (text {ReLU}^k) activation function: Barron spaces and derivative approximation
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.Application of self-adapting regularization, machine learning tools and limits in Levenberg-Marquardt algorithm to solve CNLS problem.
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.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
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.Extraction of Distribution Function of Relaxation Times by using Levenberg-Marquardt Algorithm: A New Approach to Apply a Discretization Error Free Jacobian Matrix
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.A Function Approximation Approach to the Prediction of Blood Glucose Levels
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.A function approximation approach to the prediction of blood glucose levels
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.Investigation of Electrochemical Processes in Solid Oxide Fuel Cells by Modified Levenberg-Marquardt Algorithm: A New Automatic Update Limit Strategy
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.Randomized matrix approximation to enhance regularized projection schemes in inverse problems
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.Randomized matrix approximation to enhance regularized projection schemes in inverse problems.
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).Determination of the fractional order in semilinear subdiffusion equations
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.Solving CNLS problems using Levenberg-Marquardt algorithm: A new fitting strategy combining limits and a symbolic Jacobian matrix
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.Solving CNLS problems using Levenberg-Marquardt algorithm: A new fitting strategy combining limits and a symbolic Jacobian matrix
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.Adaptive multi-parameter regularization approach to construct the distribution function of relaxation times
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.Regularized Collocation in Distribution of Diffusion Times Applied to Electrochemical Impedance Spectroscopy
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.Optimizing noisy CNLS problems by using Nelder-Mead algorithm: A new method to compute simplex step efficiency
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.Data Based Construction of Kernels for Semi-supervised Learning with Less Labels
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.Balancing principle in supervised learning for a general regularization scheme
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.Glycemic Control Indices and Their Aggregation in the Prediction of Nocturnal Hypoglycemia From Intermittent Blood Glucose Measurements
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.Prediction of nocturnal hypoglycemia by an aggregation of previously known prediction approaches: proof of concept for clinical application
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.Two-parameter regularization of ill-posed spherical pseudo-differential equations in the space of continuous functions
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.Parameter Choice Strategies for Least-squares Approximation of Noisy Smooth Functions on the Sphere
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.Pointwise Computation in an Ill-Posed Spherical Pseudo-Differential Equation
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.Regularized collocation for spherical harmonics gravitational field modeling
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.Filtered Legendre expansion method for numerical differentiation at the boundary point with application to blood glucose predictions
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.Legendre polynomials as a recommended basis for numerical differentiation in the presence of stochastic white noise
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.Blood Glucose Predictors: an Overview on How Recent Developments Help to Unlock the Problem of Glucose Regulation
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.A meta-learning approach to the regularized learning—case study: Blood glucose prediction
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.Adaptive parameter choice for one-sided finite difference schemes and its application in diabetes technology
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.The balancing principle in solving semi-discrete inverse problems in Sobolev scales by Tikhonov method
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.Assessment of Blood Glucose Predictors: The Prediction-Error Grid Analysis
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.On the generalized discrepancy principle for Tikhonov regularization in Hilbert scales
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.Estimation of linear functionals from indirect noisy data without knowledge of the noise level
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.Model functions in the modified L-curve method—case study: the heat flux reconstruction in pool boiling
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.Regularized Total Least Squares: Computational Aspects and Error Bounds
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.A Carleman estimate and the balancing principle in the quasi-reversibility method for solving the Cauchy problem for the Laplace equation
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).An analysis of Tikhonov regularization for nonlinear ill-posed problems under general smoothness assumptions
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.Regularization by projection: Approximation theoretic aspects and distance functions
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.Natural linearization for the identification of a diffusion coefficient in a quasi-linear parabolic system from short-time observations
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.An utilization of a rough approximation of a noise covariance within the framework of multi-parameter regularization
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.Randomized matrix approximation to enhance regularized projection schemes in inverse problems
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).
Regularized Reconstruction of the Order in Semilinear Subdiffusion with Memory
Regularized Reconstruction of the Order in Semilinear Subdiffusion with Memory. / Krasnoschok, Mykola; Pereverzyev, Sergei; Sergii, V et al.
Singapore: Springer, 2020. (Springer Proceedings in Mathematics & Statistics).Meta-Learning Based Blood Glucose Predictor for Diabetic Smartphone App
Meta-Learning Based Blood Glucose Predictor for Diabetic Smartphone App. / Naumova, Valeriya; Nita, Lucian; Poulsen, Jens Ulrik et al.
Springer International Publishing, 2016. (Lecture Notes in Bioengineering).
Addressing Parameter Choice Issues in Unsupervised Domain Adaptation by Aggregation
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.The balancing principle for parameter choice in distance-regularized domain adaptation
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.Reading Blood Glucose from Subcutaneous Electric Current by Means of a Regularization in Variable Reproducing Kernel Hilbert Spaces
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.Regularized Learning Algorithm for Prediction of Blood Glucose Concentration in ``No Action Period''
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).Sparsity reconstruction by means of the standard Tikhonov regularization
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.Sparsity reconstruction by means of the standard Tikhonov regularization
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.Application of Regularized Ranking and Collaborative Filtering in Predictive Alarm Algorithm for Nocturnal Hypoglycemia Prevention
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.
Data-Driven and Problem-Oriented Multiple-Kernel Learning
Data-Driven and Problem-Oriented Multiple-Kernel Learning. / Naumova, Valeriya; Pereverzyev, Sergei V.
International Workshop on advances in Regulariza- tion, Optimization, Kernel Methods and Support Vector Machines: theory and applications. 2013.Assessment of blood glucose predictors: the Prediction-Error Grid Analysis (PRED-EGA)
Assessment of blood glucose predictors: the Prediction-Error Grid Analysis (PRED-EGA). / Sivananthan, S; Naumova, V; Man, C Dalla et al.
The 4th International Conference on Advanced Technologies & Treatments in Diabetes. 2011.
General regularization in covariate shift adaptation
General regularization in covariate shift adaptation. / Nguyen, Duc Hoan; Pereverzyev, Sergiy; Zellinger, Werner et al.
Data-driven Models in Inverse Problems. Band 31 Berlin/Boston: Walter de Gruyter GmbH, 2025. S. 245-270 (Radon Series on Computational and Applied Mathematics).Regularized Quadrature Methods for Fredholm Integral Equations of the First Kind
Regularized Quadrature Methods for Fredholm Integral Equations of the First Kind. / Sergei, V; Pereverzyev, Evgeniya V; Tkachenko, Semenova and Pavlo et al.
Contemporary Computational Mathematics - A Celebration of the 80th Birthday of Ian Sloan. Springer, 2019.Regularized Quadrature Methods for Fredholm Integral Equations of the First Kind.
Regularized Quadrature Methods for Fredholm Integral Equations of the First Kind. / Sergei, V; Pereverzyev, Evgeniya Semenova and Pavlo Tkachenko; Dick, Josef (Herausgeber:in) et al.
Contemporary Computational Mathematics - A Celebration of the 80th Birthday of Ian Sloan. Springer, 2018.Regularization of naturally linearized parameter identification problems and the application of the balancing principle
Regularization of naturally linearized parameter identification problems and the application of the balancing principle. / Pereverzyev, Hui Cao and Sergei; Wang, Yanfei (Herausgeber:in); Anatoly, G (Herausgeber:in) et al.
Optimization and regularization for computational inverse problems and applications. Springer, 2010. S. 65-106.
Two-parameter regularization of ill-posed spherical pseudo-differential equations in the space of continuous functions
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.Filtered Legendre Expansion Method for Numerical Differentiation at the Boundary Point with Application to Blood Glucose Predictions
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.Adaptive parameter choice for one-sided finite difference schemes and its application in diabetes technology
Adaptive parameter choice for one-sided finite difference schemes and its application in diabetes technology. / Naumova, Valeriya; Pereverzyev, Sergei; Sampath, Sivananthan.
2011. 20 S.