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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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V. Naumova and K. Schnass

Dictionary Learning from Incomplete Data for Efficient Image Restoration

In 2017 25th European Signal Processing Conference (EUSIPCO). IEEE, 2017.
Proceedings, refereed
2017
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V. Naumova, S. V. Pereverzyev and S. Sampath

Reading blood glucose from subcutaneous electric current by means of a regularization in variable Reproducing Kernel Hilbert Spaces

In IEEE Conference on Decision and Control and European Control Conference. IEEE, 2011.
Proceedings, refereed
2011
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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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Export 24 results:
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

Talks, invited

M. Fornasier, E. De Vito, Z. Kereta and V. Naumova

Automated parameter estimation for selected inverse problems

In Grenoble, France, 2019.
Status: Published
Z. Kereta, T. Klock and V. Naumova

Covariance and precision matrix estimation, and dimension reduction in regression problems

In Oslo, Norway, 2019.
Status: Published
Z. Kereta, T. Klock and V. Naumova

Towards nonlinear sufficient dimension reduction

In AIP conference, Grenoble, France, 2019.
Status: Published
2018

Talks, invited

V. Naumova and Z. Kereta

A machine learning approach to optimal regularization: Affine Manifolds

In NTNU, Norway, 2018.
Status: Published
V. Naumova and T. Klock

Multi-parameter regularization for solving inverse problems of unmixing type

In University of Cambridge, UK, 2018.
Status: Published
V. Naumova and Z. Kereta

A machine learning approach to optimal regularization

In European Women in Mathematics, Graz, Austria, 2018.
Status: Published
V. Naumova and Z. Kereta

A machine learning approach for adaptive parameter selection

In University of Oslo, Norway, 2018.
Status: Published
2017

Proceedings, refereed

V. Naumova and K. Schnass

Dictionary Learning from Incomplete Data for Efficient Image Restoration

In 2017 25th European Signal Processing Conference (EUSIPCO). IEEE, 2017.
Status: Published