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Most recent publications

E. De Vito, Z. Kereta, V. Naumova, L. Rosasco and S. Vigogna

Monte Carlo wavelets: a randomized approach to frame discretization

In Sampling Theory and Applications. IEEE, 2019.
Proceedings, refereed
2019
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P. M. Florvaag, V. Naumova and K. Valen-Sendstad

Automated and objective segmentation of medical image using machine learning techniques: all models are wrong, but some are useful

In Computational and Mathematical Biomedical Engineering. Sendai, Japan: CMBE, 2019.
Proceedings, refereed
2019
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Selected publications

V. Naumova

Numerical Methods for Diabetes Technology

In Mathematical Algorithms for a Better Management of Type 1 Diabetes. Germany: LAP LAMBERT Academic Publishing, 2012.
Book
2012
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V. Naumova and S. Peter

Minimization of Multi-Penalty Functionals by Alternating Iterative Thresholding and Optimal Parameter Choices

Inverse Problems 30 (2014): 1-35.
Journal Article
2014
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V. Naumova, S. V. Pereverzyev and S. Sampath

A meta-learning approach to the regularized learning—Case study: Blood glucose prediction

Neural Networks 33 (2012): 181-193.
Journal Article
2012
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News

24 February 2020

Applications open for MLCC2020!

Background

PhD in Natural Sciences (Applied Mathematics)
Johannes Kepler University Linz and Johann Radon Institute for Computational and Applied Mathematics, Austrian Academy of Sciences
December 2012

Students under supervision

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2019

Proceedings, refereed

E. De Vito, Z. Kereta, V. Naumova, L. Rosasco and S. Vigogna

Monte Carlo wavelets: a randomized approach to frame discretization

In Sampling Theory and Applications. IEEE, 2019.
Status: Published
P. M. Florvaag, V. Naumova and K. Valen-Sendstad

Automated and objective segmentation of medical image using machine learning techniques: all models are wrong, but some are useful

In Computational and Mathematical Biomedical Engineering. Sendai, Japan: CMBE, 2019.
Status: Published