Information complexity of equations of the second kind with compact operators in Hilbert space. - Sergei V. Pereverzev; Cosnazar C. Scharipov (J. Complex., 1992)

On Optimization of Direct Methods of Solving Weakly Singular Integral Equations. - Sergei V. Pereverzev; Sergei G. Solodky (J. Complex., 1993)

Optimization of Projection Methods for Solving Ill-Posed Problems. - Sergei V. Pereverzyev (Computing, 1995)

Optimization of Methods for Approximate Solution of Operator Equations. - Sergei V. Pereverzev (Nova Science Publishers, 1996)

Information Complexity of Multivariate Fredholm Integral Equations in Sobolev Classes. - Karin Frank; Stefan Heinrich; Sergei V. Pereverzev (J. Complex., 1996)

The Minimal Radius of Galerkin Information for the Fredholm Problem of the First Kind. - Sergei V. Pereverzev; Sergei G. Solodky (J. Complex., 1996)

Brakhage's Implicit Iteration Method and the Information Complexity of Equations with Operators Having Closed Range. - Sergei V. Pereverzev; Eberhard Schock (J. Complex., 1999)

An adaptive discretization for Tikhonov-Phillips regularization with a posteriori parameter selection. - Peter Maaß; Sergei V. Pereverzev; Ronny Ramlau; Sergei G. Solodky (Numerische Mathematik, 2001)

Optimal Discretization of Inverse Problems in Hilbert Scales. Regularization and Self-Regularization of Projection Methods. - Peter Mathé; Sergei V. Pereverzev (SIAM J. Numer. Anal., 2001)

Stable Summation of Orthogonal Series with Noisy Coefficients. - Peter Mathé; Sergei V. Pereverzev (J. Approx. Theory, 2002)

Direct Estimation of Linear Functionals from Indirect Noisy Observations. - Peter Mathé; Sergei V. Pereverzev (J. Complex., 2002)

Dagstuhl 2000. - Sergei V. Pereverzev; Grzegorz W. Wasilkowski (J. Complex., 2002)

Self-regularization by projection for noisy pseudodifferential equations of negative order. - Helmut Harbrecht; Sergei V. Pereverzev; Reinhold Schneider (Numerische Mathematik, 2003)

On the Adaptive Selection of the Parameter in Regularization of Ill-Posed Problems. - Sergei V. Pereverzev; Eberhard Schock (SIAM J. Numer. Anal., 2005)

The discretized discrepancy principle under general source conditions. - Peter Mathé; Sergei V. Pereverzev (J. Complex., 2006)

Numerical differentiation from a viewpoint of regularization theory. - Shuai Lu; Sergei V. Pereverzev (Math. Comput., 2006)

Regularization of some linear ill-posed problems with discretized random noisy data. - Peter Mathé; Sergei V. Pereverzev (Math. Comput., 2006)

On regularization algorithms in learning theory. - Frank Bauer; Sergei V. Pereverzev; Lorenzo Rosasco (J. Complex., 2007)

Regularized collocation method for Fredholm integral equations of the first kind. - M. Thamban Nair; Sergei V. Pereverzev (J. Complex., 2007)

On the balancing principle for some problems of Numerical Analysis. - Raytcho D. Lazarov; Shuai Lu; Sergei V. Pereverzev (Numerische Mathematik, 2007)

The use of higher order finite difference schemes is not dangerous. - Peter Mathé; Sergei V. Pereverzev (J. Complex., 2009)

Sparse recovery by the standard Tikhonov method. - Shuai Lu; Sergei V. Pereverzev (Numerische Mathematik, 2009)

Regularized Total Least Squares: Computational Aspects and Error Bounds. - Shuai Lu; Sergei V. Pereverzev; Ulrich Tautenhahn (SIAM J. Matrix Anal. Appl., 2009)

Adaptive Kernel Methods Using the Balancing Principle. - Ernesto De Vito; Sergei V. Pereverzyev; Lorenzo Rosasco (Found. Comput. Math., 2010)

Reading blood glucose from subcutaneous electric current by means of a regularization in variable Reproducing Kernel Hilbert Spaces. - Valeriya Naumova; Sergei V. Pereverzyev; Sivananthan Sampath (CDC/ECC, 2011)

Multi-parameter regularization and its numerical realization. - Shuai Lu; Sergei V. Pereverzev (Numerische Mathematik, 2011)

Adaptive parameter choice for one-sided finite difference schemes and its application in diabetes technology. - Valeriya Naumova; Sergei V. Pereverzyev; Sivananthan Sivananthan (J. Complex., 2012)

A meta-learning approach to the regularized learning - Case study: Blood glucose prediction. - Valeriya Naumova; Sergei V. Pereverzyev; Sivananthan Sivananthan (Neural Networks, 2012)

Filtered Legendre expansion method for numerical differentiation at the boundary point with application to blood glucose predictions. - Hrushikesh Narhar Mhaskar; Valeriya Naumova; Sergei V. Pereverzyev (Appl. Math. Comput., 2013)

Discretized Tikhonov regularization for Robin boundaries localization. - Hui Cao; Sergei V. Pereverzev; Eva Sincich (Appl. Math. Comput., 2014)

Parameter Choice Strategies for Multipenalty Regularization. - Massimo Fornasier; Valeriya Naumova; Sergei V. Pereverzyev (SIAM J. Numer. Anal., 2014)

Pointwise Computation in an Ill-Posed Spherical Pseudo-Differential Equation. - Sergei V. Pereverzyev; Pavlo Tkachenko (Comput. Methods Appl. Math., 2015)

Parameter Choice Strategies for Least-squares Approximation of Noisy Smooth Functions on the Sphere. - Sergei V. Pereverzyev; Ian H. Sloan; Pavlo Tkachenko (SIAM J. Numer. Anal., 2015)

Two-parameter regularization of ill-posed spherical pseudo-differential equations in the space of continuous functions. - Hui Cao; Sergei V. Pereverzyev; Ian H. Sloan; Pavlo Tkachenko (Appl. Math. Comput., 2016)

Prediction of nocturnal hypoglycemia by an aggregation of previously known prediction approaches: proof of concept for clinical application. - Pavlo Tkachenko; Galyna Kriukova; Marharyta Aleksandrova; Oleg Chertov; Eric Renard; Sergei V. Pereverzyev (Comput. Methods Programs Biomed., 2016)

On the convergence rate and some applications of regularized ranking algorithms. - Galyna Kriukova; Sergei V. Pereverzyev; Pavlo Tkachenko (J. Complex., 2016)

A linear functional strategy for regularized ranking. - Galyna Kriukova; Oleksandra Panasiuk; Sergei V. Pereverzyev; Pavlo Tkachenko (Neural Networks, 2016)

Application of regularized ranking and collaborative filtering in predictive alarm algorithm for nocturnal hypoglycemia prevention. - Galyna Kriukova; Nadiya Shvai; Sergei V. Pereverzyev (IDAACS, 2017)

A Deep Learning Approach to Diabetic Blood Glucose Prediction. - Hrushikesh N. Mhaskar; Sergei V. Pereverzyev; Maria D. van der Walt (Frontiers Appl. Math. Stat., 2017)

Regularization by the Linear Functional Strategy with Multiple Kernels. - Sergei V. Pereverzyev; Pavlo Tkachenko (Frontiers Appl. Math. Stat., 2017)

Complexity of linear ill-posed problems in Hilbert space. - Peter Mathé; Sergei V. Pereverzev (J. Complex., 2017)

Data Based Construction of Kernels for Semi-Supervised Learning With Less Labels. - Hrushikesh N. Mhaskar; Sergei V. Pereverzyev; Vasyl Yu. Semenov; Evgeniya V. Semenova (Frontiers Appl. Math. Stat., 2019)

Regularized Collocation in Distribution of Diffusion Times Applied to Electrochemical Impedance Spectroscopy. - Sergei V. Pereverzev; Sergei G. Solodky; Vitalii B. Vasylyk; Mark Zic (Comput. Methods Appl. Math., 2020)

The balancing principle for parameter choice in distance-regularized domain adaptation. - Werner Zellinger; Natalia Shepeleva; Marius-Constantin Dinu; Hamid Eghbal-zadeh; Hoan Duc Nguyen; Bernhard Nessler; Sergei V. Pereverzyev; Bernhard Alois Moser (NeurIPS, 2021)

A Function Approximation Approach to the Prediction of Blood Glucose Levels. - Hrushikesh N. Mhaskar; Sergei V. Pereverzyev; Maria D. van der Walt (Frontiers Appl. Math. Stat., 2021)

Addressing Parameter Choice Issues in Unsupervised Domain Adaptation by Aggregation. - 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 (ICLR, 2023)

Domain Generalization by Functional Regression. - Markus Holzleitner; Sergei V. Pereverzyev; Werner Zellinger (CoRR, 2023)

General regularization in covariate shift adaptation. - Hoan Duc Nguyen; Sergei V. Pereverzyev; Werner Zellinger (CoRR, 2023)

On regularized Radon-Nikodym differentiation. - Duc Hoan Nguyen; Werner Zellinger; Sergei V. Pereverzyev (CoRR, 2023)

Adaptive Learning of Density Ratios in RKHS. - Werner Zellinger; Stefan Kindermann 001; Sergei V. Pereverzyev (J. Mach. Learn. Res., 2023)

Multiparameter regularization and aggregation in the context of polynomial functional regression. - Elke Ruth Gizewski; Markus Holzleitner; Lukas Mayer-Suess; Sergiy Pereverzyev Jr.; Sergei V. Pereverzyev (CoRR, 2024)

On regularized polynomial functional regression. - Markus Holzleitner; Sergei V. Pereverzyev (J. Complex., 2024)

Two-layer networks with the ReLUk activation function: Barron spaces and derivative approximation. - Yuanyuan Li; Shuai Lu; Peter Mathé; Sergei V. Pereverzev (Numerische Mathematik, 2024)