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ORCIDSergei V. Pereverzyev
Person information
- affiliation: Austrian Academy of Sciences, Institute for Computational and Applied Mathematics (RICAM), Linz, Austria
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Books and Theses
- 1996
[b1]Sergei V. Pereverzev:
Optimization of Methods for Approximate Solution of Operator Equations. Nova Science Publishers 1996, ISBN 978-1-56072-140-6, pp. 1-352
Journal Articles
- 2024
- [j43]Markus Holzleitner, Sergei V. Pereverzyev:
On regularized polynomial functional regression. J. Complex. 83: 101853 (2024) - [j42]Yuanyuan Li, Shuai Lu, Peter Mathé, Sergei V. Pereverzev:
Two-layer networks with the ReLUk activation function: Barron spaces and derivative approximation. Numerische Mathematik 156(1): 319-344 (2024) - 2021
- [j41]Hrushikesh N. Mhaskar, Sergei V. Pereverzyev
, Maria D. van der Walt:
A Function Approximation Approach to the Prediction of Blood Glucose Levels. Frontiers Appl. Math. Stat. 7: 707884 (2021) - 2020
- [j40]Sergei V. Pereverzev, Sergei G. Solodky, Vitalii B. Vasylyk, Mark Zic:
Regularized Collocation in Distribution of Diffusion Times Applied to Electrochemical Impedance Spectroscopy. Comput. Methods Appl. Math. 20(3): 517-530 (2020) - 2019
- [j39]Hrushikesh N. Mhaskar, Sergei V. Pereverzyev, Vasyl Yu. Semenov, Evgeniya V. Semenova:
Data Based Construction of Kernels for Semi-Supervised Learning With Less Labels. Frontiers Appl. Math. Stat. 5: 21 (2019) - 2017
- [j38]Sergei V. Pereverzyev, Pavlo Tkachenko:
Regularization by the Linear Functional Strategy with Multiple Kernels. Frontiers Appl. Math. Stat. 3: 1 (2017) - [j37]Hrushikesh N. Mhaskar, Sergei V. Pereverzyev, Maria D. van der Walt:
A Deep Learning Approach to Diabetic Blood Glucose Prediction. Frontiers Appl. Math. Stat. 3: 14 (2017) - [j36]Peter Mathé, Sergei V. Pereverzev:
Complexity of linear ill-posed problems in Hilbert space. J. Complex. 38: 50-67 (2017) - 2016
- [j35]Hui Cao, Sergei V. Pereverzyev, Ian H. Sloan, Pavlo Tkachenko:
Two-parameter regularization of ill-posed spherical pseudo-differential equations in the space of continuous functions. Appl. Math. Comput. 273: 993-1005 (2016) - [j34]Pavlo Tkachenko, Galyna Kriukova, Marharyta Aleksandrova, Oleg Chertov, Eric Renard, Sergei V. Pereverzyev:
Prediction of nocturnal hypoglycemia by an aggregation of previously known prediction approaches: proof of concept for clinical application. Comput. Methods Programs Biomed. 134: 179-186 (2016) - [j33]Galyna Kriukova, Sergei V. Pereverzyev, Pavlo Tkachenko:
On the convergence rate and some applications of regularized ranking algorithms. J. Complex. 33: 14-29 (2016) - [j32]Galyna Kriukova, Oleksandra Panasiuk, Sergei V. Pereverzyev, Pavlo Tkachenko:
A linear functional strategy for regularized ranking. Neural Networks 73: 26-35 (2016) - 2015
- [j31]Sergei V. Pereverzyev, Pavlo Tkachenko:
Pointwise Computation in an Ill-Posed Spherical Pseudo-Differential Equation. Comput. Methods Appl. Math. 15(2): 213-219 (2015) - [j30]Sergei V. Pereverzyev, Ian H. Sloan, Pavlo Tkachenko:
Parameter Choice Strategies for Least-squares Approximation of Noisy Smooth Functions on the Sphere. SIAM J. Numer. Anal. 53(2): 820-835 (2015) - 2014
- [j29]Hui Cao, Sergei V. Pereverzev, Eva Sincich:
Discretized Tikhonov regularization for Robin boundaries localization. Appl. Math. Comput. 226: 374-385 (2014) - [j28]Massimo Fornasier, Valeriya Naumova, Sergei V. Pereverzyev:
Parameter Choice Strategies for Multipenalty Regularization. SIAM J. Numer. Anal. 52(4): 1770-1794 (2014) - 2013
- [j27]Hrushikesh Narhar Mhaskar, Valeriya Naumova, Sergei V. Pereverzyev:
Filtered Legendre expansion method for numerical differentiation at the boundary point with application to blood glucose predictions. Appl. Math. Comput. 224: 835-847 (2013) - 2012
- [j26]Valeriya Naumova, Sergei V. Pereverzyev, Sivananthan Sivananthan:
Adaptive parameter choice for one-sided finite difference schemes and its application in diabetes technology. J. Complex. 28(5-6): 524-538 (2012) - [j25]Valeriya Naumova, Sergei V. Pereverzyev, Sivananthan Sivananthan:
A meta-learning approach to the regularized learning - Case study: Blood glucose prediction. Neural Networks 33: 181-193 (2012) - 2011
- [j24]Shuai Lu, Sergei V. Pereverzev:
Multi-parameter regularization and its numerical realization. Numerische Mathematik 118(1): 1-31 (2011) - 2010
- [j23]Ernesto De Vito, Sergei V. Pereverzyev, Lorenzo Rosasco:
Adaptive Kernel Methods Using the Balancing Principle. Found. Comput. Math. 10(4): 455-479 (2010) - 2009
- [j22]Peter Mathé, Sergei V. Pereverzev:
The use of higher order finite difference schemes is not dangerous. J. Complex. 25(1): 3-10 (2009) - [j21]Shuai Lu, Sergei V. Pereverzev:
Sparse recovery by the standard Tikhonov method. Numerische Mathematik 112(3): 403-424 (2009) - [j20]Shuai Lu, Sergei V. Pereverzev, Ulrich Tautenhahn:
Regularized Total Least Squares: Computational Aspects and Error Bounds. SIAM J. Matrix Anal. Appl. 31(3): 918-941 (2009) - 2007
- [j19]Frank Bauer, Sergei V. Pereverzev, Lorenzo Rosasco:
On regularization algorithms in learning theory. J. Complex. 23(1): 52-72 (2007) - [j18]M. Thamban Nair, Sergei V. Pereverzev:
Regularized collocation method for Fredholm integral equations of the first kind. J. Complex. 23(4-6): 454-467 (2007) - [j17]Raytcho D. Lazarov, Shuai Lu, Sergei V. Pereverzev:
On the balancing principle for some problems of Numerical Analysis. Numerische Mathematik 106(4): 659-689 (2007) - 2006
- [j16]Peter Mathé, Sergei V. Pereverzev:
The discretized discrepancy principle under general source conditions. J. Complex. 22(3): 371-381 (2006) - [j15]Shuai Lu, Sergei V. Pereverzev:
Numerical differentiation from a viewpoint of regularization theory. Math. Comput. 75(256): 1853-1870 (2006) - [j14]Peter Mathé, Sergei V. Pereverzev:
Regularization of some linear ill-posed problems with discretized random noisy data. Math. Comput. 75(256): 1913-1929 (2006) - 2005
- [j13]Sergei V. Pereverzev, Eberhard Schock:
On the Adaptive Selection of the Parameter in Regularization of Ill-Posed Problems. SIAM J. Numer. Anal. 43(5): 2060-2076 (2005) - 2003
- [j12]Helmut Harbrecht, Sergei V. Pereverzev, Reinhold Schneider:
Self-regularization by projection for noisy pseudodifferential equations of negative order. Numerische Mathematik 95(1): 123-143 (2003) - 2002
- [j11]Peter Mathé, Sergei V. Pereverzev:
Stable Summation of Orthogonal Series with Noisy Coefficients. J. Approx. Theory 118(1): 66-80 (2002) - [j10]Sergei V. Pereverzev, Grzegorz W. Wasilkowski:
Dagstuhl 2000. J. Complex. 18(2): 393- (2002) - [j9]Peter Mathé, Sergei V. Pereverzev:
Direct Estimation of Linear Functionals from Indirect Noisy Observations. J. Complex. 18(2): 500-516 (2002) - 2001
- [j8]Peter Maaß, Sergei V. Pereverzev, Ronny Ramlau, Sergei G. Solodky:
An adaptive discretization for Tikhonov-Phillips regularization with a posteriori parameter selection. Numerische Mathematik 87(3): 485-502 (2001) - [j7]Peter Mathé, Sergei V. Pereverzev:
Optimal Discretization of Inverse Problems in Hilbert Scales. Regularization and Self-Regularization of Projection Methods. SIAM J. Numer. Anal. 38(6): 1999-2021 (2001) - 1999
- [j6]Sergei V. Pereverzev, Eberhard Schock:
Brakhage's Implicit Iteration Method and the Information Complexity of Equations with Operators Having Closed Range. J. Complex. 15(3): 385-401 (1999) - 1996
- [j5]Karin Frank, Stefan Heinrich, Sergei V. Pereverzev:
Information Complexity of Multivariate Fredholm Integral Equations in Sobolev Classes. J. Complex. 12(1): 17-34 (1996) - [j4]Sergei V. Pereverzev, Sergei G. Solodky:
The Minimal Radius of Galerkin Information for the Fredholm Problem of the First Kind. J. Complex. 12(4): 401-415 (1996) - 1995
- [j3]Sergei V. Pereverzyev:
Optimization of Projection Methods for Solving Ill-Posed Problems. Computing 55(2): 113-124 (1995) - 1993
- [j2]Sergei V. Pereverzev, Sergei G. Solodky:
On Optimization of Direct Methods of Solving Weakly Singular Integral Equations. J. Complex. 9(2): 313-325 (1993) - 1992
- [j1]Sergei V. Pereverzev, Cosnazar C. Scharipov:
Information complexity of equations of the second kind with compact operators in Hilbert space. J. Complex. 8(2): 176-202 (1992)
Conference and Workshop Papers
- 2023
- [c4]Marius-Constantin Dinu, Markus Holzleitner, Maximilian Beck, Hoan Duc Nguyen, Andrea Huber, Hamid Eghbal-zadeh, Bernhard Alois Moser, Sergei V. Pereverzyev, Sepp Hochreiter, Werner Zellinger:
Addressing Parameter Choice Issues in Unsupervised Domain Adaptation by Aggregation. ICLR 2023 - 2021
- [c3]Werner Zellinger, Natalia Shepeleva, Marius-Constantin Dinu, Hamid Eghbal-zadeh, Hoan Duc Nguyen, Bernhard Nessler, Sergei V. Pereverzyev, Bernhard Alois Moser:
The balancing principle for parameter choice in distance-regularized domain adaptation. NeurIPS 2021: 20798-20811 - 2017
- [c2]Galyna Kriukova, Nadiya Shvai, Sergei V. Pereverzyev:
Application of regularized ranking and collaborative filtering in predictive alarm algorithm for nocturnal hypoglycemia prevention. IDAACS 2017: 634-638 - 2011
- [c1]Valeriya Naumova, Sergei V. Pereverzyev, Sivananthan Sampath:
Reading blood glucose from subcutaneous electric current by means of a regularization in variable Reproducing Kernel Hilbert Spaces. CDC/ECC 2011: 5158-5163
Informal and Other Publications
- 2024
- [i9]Elke Ruth Gizewski, Markus Holzleitner, Lukas Mayer-Suess, Sergiy Pereverzyev Jr., Sergei V. Pereverzyev:
Multiparameter regularization and aggregation in the context of polynomial functional regression. CoRR abs/2405.04147 (2024) - 2023
- [i8]Markus Holzleitner, Sergei V. Pereverzyev, Werner Zellinger:
Domain Generalization by Functional Regression. CoRR abs/2302.04724 (2023) - [i7]Marius-Constantin Dinu, Markus Holzleitner, Maximilian Beck, Hoan Duc Nguyen, Andrea Huber, Hamid Eghbal-zadeh, Bernhard Alois Moser, Sergei V. Pereverzyev, Sepp Hochreiter, Werner Zellinger:
Addressing Parameter Choice Issues in Unsupervised Domain Adaptation by Aggregation. CoRR abs/2305.01281 (2023) - [i6]Hoan Duc Nguyen, Sergei V. Pereverzyev, Werner Zellinger:
General regularization in covariate shift adaptation. CoRR abs/2307.11503 (2023) - [i5]Werner Zellinger, Stefan Kindermann, Sergei V. Pereverzyev:
Adaptive learning of density ratios in RKHS. CoRR abs/2307.16164 (2023) - [i4]Duc Hoan Nguyen, Werner Zellinger, Sergei V. Pereverzyev:
On regularized Radon-Nikodym differentiation. CoRR abs/2308.07887 (2023) - [i3]Markus Holzleitner, Sergei V. Pereverzyev:
On regularized polynomial functional regression. CoRR abs/2311.03036 (2023) - 2021
- [i2]Hrushikesh N. Mhaskar, Sergei V. Pereverzyev, Maria D. van der Walt:
A function approximation approach to the prediction of blood glucose levels. CoRR abs/2105.05893 (2021) - 2017
- [i1]Hrushikesh N. Mhaskar, Sergei V. Pereverzyev, Maria D. van der Walt:
A deep learning approach to diabetic blood glucose prediction. CoRR abs/1707.05828 (2017)
Coauthor Index
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