Prof. Dr. Sergei Pereverzyev

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Sergei Pereverzyev

Peer Reviewed Journal Publication
  • 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. (link)
  • 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'>. (link)
  • 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'>. (link)
  • Sampath, Sivananthan; Tkachenko, Pavlo; Renard, Eric; Pereverzev, Sergei V. (2016, online: 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'>. (link)
  • 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'>. (link)
  • 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.
  • 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. (link)
  • 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. (link)
  • Pereverzyev, S. V.; Sloan, I. H.; Tkachenko, P. (2015, online: 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. (link)
  • Pereverzyev, S. V.; Tkachenko, P. (2015, online: 2015) Pointwise Computation in an Ill-Posed Spherical Pseudo-Differential Equation. Computational Methods in Applied Mathematics, Bd. 15 (2), S. 213–219. (link)
  • Fornasier, Massimo; Naumova, Valeriya; Pereverzyev, Sergei (2014, online: 2014) Parameter choice strategies for multipenalty regularization. SIAM Journal on Numerical Analysis, Bd. 52 (4), S. 1770-1794. (link)
  • 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. (link)
  • 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.
  • Mhaskar, Hrushikesh; Naumova, Valeriya; Pereverzyev, Sergei (2013, online: 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. (link)
  • Naumova, Valeriya; Pereverzyev, Sergei V. (2013, online: 2013) Multi-penalty regularization with a component-wise penalization. Inverse Problems, Bd. 29 (7), S. 1-16. (link)
  • 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. (link)
  • Naumova, V.; Pereverzyev, S. V. (2012, online: 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.
  • 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. (link)
  • Naumova, V.; Pereverzyev, S. V.; Sampath, S. (2012, online: 2012) Adaptive parameter choice for one-sided finite difference schemes and its application in diabetes technology. Journal of Complexity, Bd. 28, S. 524-538. (link)
  • 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. (link)
  • 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. (link)
  • 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. (link)
  • Lu, Shuai; Pereverzev, Sergei V. (2011) Multi-parameter regularization and its numerical realization. Numerische Mathematik, Bd. 118 (1), S. 1-31. (link)
  • (2010) On the generalized discrepancy principle for Tikhonov regularization in Hilbert scales. Journal of Integral Equations and Applications, Bd. 22 (3), S. 483-517. (link)
  • 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.
  • 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. (link)
  • 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. (link)
  • 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. (link)
  • Pereverzyev, Shuai Lu and Sergei V (2009) Sparse recovery by the standard Tikhonov method. Numerische Mathematik, Bd. 112 (3), S. 403-424. (link)
  • 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. (link)
  • 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). (link)
  • 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. (link)
  • 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. (link)
  • 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. (link)
  • Hui Cao, Sergei V. Pereverzyev (2007) The balancing principle for the regularization of elliptic Cauchy problems. Inverse Problems, Bd. 23, S. 1943-1961. (link)
  • 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. (link)
  • F. Bauer, P. Mathe, S. Pereverzyev (2007) Local solutions to Inverse Problems in Geodesy. Journal of Geodesy, Bd. 81.
  • 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. (link)
  • 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. (link)
  • 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.
  • S. Lu, S. Pereverzyev (2006) Numerical differentiation from a view point of Regularization Theory. Mathematics of Computations, Bd. 75, S. 1853-1870. (link)
  • P. Mathe, S. Pereverzyev (2006) The discretized discrepancy principle under general source conditions. Journal of Complexity, Bd. 22, S. 371-381. (link)
  • Nair, T.; Pereverzyev, S.; Tauthenhahn, U. (2005) Regularization in Hilbert scales under general smoothing conditions. Inverse Problems, Bd. 21(6), S. 1851-1871.
  • 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.
  • 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.
  • 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.
  • 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'>. (link)

Book/Monograph
  • Naumova, Valeriya; Nita, Lucian; Poulsen, Jens Ulrik; Pereverzyev, Sergei V. (2016, online: 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. (link)
  • Pereverzyev, Sergiy V.; Lu, Shuai (2013, online: 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). (link)
  • 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). (link)

Conference Contribution: Publication in Proceedings
  • 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.
  • 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.
  • Hui, Cao; Sergei, Pereverzyev; Eva, Sincich (2008) Natural liearization for corrosion identification., ICIPE proceedings In Reihe: ICIPE proceedings: IOP.
  • 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. (link)
  • 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)).
  • 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)
  • Naumova, Valeriya; Pereverzyev, Sergei V. (2013, online: 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 . (link)
  • 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
  • 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. (link)

Editorship
  • (2008) Dual regularized total least squares and multi-parameter regularization. In Reihe: Dedicated to Professor G. Vainikko on the occasion of his 70th birthday. (link)
  • (2008) The use of higher order finite difference schemes is not dangerous. (link)

Research Report
  • Kriukova, Galyna; Panasiuk, Oleksandra; Pereverzyev, Sergei V.; Tkachenko, Pavlo (2015) A Linear Functional Strategy for Regularized Ranking. Bericht-Nr. 2015-13; RICAM: Linz. (link)
  • Kriukova, Galyna; Pereverzyev, Sergei V.; Tkachenko, Pavlo (2014, online: 2014) On the convergence rate and some applications of regularized ranking algorithms. Bericht-Nr. 2014-21; RICAM: Linz. (link)
  • Cao, Hui; Pereverzyev, Sergei; Sloan, Ian H.; Tkachenko, Pavlo (2014, online: 2014) Two-parameter regularization of ill-posed spherical pseudo-differential equations in the space of continuous functions. Bericht-Nr. 2014-17; RICAM: Linz. (link)
  • Pereverzyev, Sergiy V.; Tkachenko, Pavlo (2014, online: 2014) Approximation of the solution of an ill-posed spherical pseudo-differential equation at a given point. RICAM: Linz. (link)
  • Pereverzyev, Sergei V.; Sloan, Ian H.; Tkachenko, Pavlo (2014, online: 2014) Parameter choice strategies for least-squares approximation of noisy smooth functions on the sphere. Bericht-Nr. 2014-04; RICAM: Linz. (link)
  • Naumova, Valeriya; Pereverzyev, Sergei V.; Tkachenko, Pavlo (2013, online: 2013) Regularized collocation for Spherical harmonics Gravitational Field Modeling. Bericht-Nr. 2013-12; RICAM: Linz. (link)
  • Fornasier, Massimo; Naumova, Valeriya; Pereverzyev, Sergei (2013, online: 2013) Parameter Choice Strategies for Multi-Penalty Regularization. Bericht-Nr. RICAM Report No 2013-10; RICAM: Linz . (link)
  • Mhaskar, Hrushikesh; Naumova, Valeriya; Pereverzyev, Sergei V. (2013, online: 2013) Filtered Legendre Expansion Method for Numerical Differentiation at the Boundary Point with Application to Blood Glucose Predictions. Bericht-Nr. 2013-07; RICAM: Linz. (link)
  • Naumova, Valeriya; Pereverzyev, Sergei (2013, online: 2013) Multi-Penalty Regularization with a Component-Wise Penalization. Bericht-Nr. 2013-03; RICAM: Linz. (link)
  • 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. (link)
  • Naumova, V.; Pereverzyev, S.; Sampath, S. (2012, online: 2012) Regularization in Variable RKHSs with application to the Blood Glucose Reading. Bericht-Nr. 51/2012; Mathematisches Forschungsinstitut Oberwolfach: Oberwolfach. (link)
  • Naumova, V.; Pereverzyev, S.; Sampath, S. (2012, online: 2012) A Meta-Learning Approach to the Adaptive Regularization – Case Study: Blood Glucose Prediction. Bericht-Nr. 51/2012; Mathematisches Forschungsinstitut Oberwolfach: Oberwolfach. (link)
  • Pereverzyev, S. V.; Naumova, V.; Sampath, S. (2012, online: 2012) Learning in Variable RKHSs with application to the Blood Glucose Reading. Bericht-Nr. 31/2012; Oberwolfach. (link)
  • Lu, S.; Naumova, V.; Pereverzyev, S.V. (2012, online: 2012) Numerical differentiation by means of Legendre polynomials in the presence of square summable noise. Bericht-Nr. 2012-15; Linz. (link)
  • 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.
  • 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;. (link)
  • Naumova, Valeriya; Pereverzev, Sergei; Sampath, Sivananthan (2011) Extrapolation in variable RKHSs with application to the BG reading. Bericht-Nr. 2011-04; RICAM:. (link)
  • 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;. (link)
  • 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;. (link)
  • Lu, Shuai; Pereverzyev, Sergei V (2009) Multi-parameter regularization and its numerical realization. Bericht-Nr. 2009-11;. (link)
  • Shuai Lu, Sergei V. Pereverzyev (2008) Sparsity reconstruction by the standard Tikhonov method. Bericht-Nr. 2008-17;. (link)
  • Shuai Lu, Sergei V. Pereverzyev, Ulrich Tautenhahn (2008) A model function method in total least squares. Bericht-Nr. 2008-18;. (link)