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Most recent publications

V. Naumova

Multi-parameter regularisation for solving unmixing problems in signal processing: theoretical and practical aspects

In Mathematical Signal Processing and Data Analysis, Bremen, Germany, 2017.
Talk, keynote
2017
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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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2017

Talks, keynote

V. Naumova

Multi-parameter regularisation for solving unmixing problems in signal processing: theoretical and practical aspects

In Mathematical Signal Processing and Data Analysis, Bremen, Germany, 2017.
Status: Published

Talks, invited

V. Naumova

Image separation using multi-penalty regularization

In CEA Saclay, France, 2017.
Status: Published
V. Naumova

Advanced statistics and data analysis for blood glucose prediction and diabetes

In Universitäres Herzzentrum Hamburg, Germany, 2017.
Status: Accepted
V. Naumova

Innovative solution of unmixing problems by means of multi-penalty regularization

In Applied Inverse Problems, Hangzhou, China, 2017.
Status: Published
V. Naumova

A machine learning approach to optimal regularization: affine manifolds

In International Workshop Dictionary Learning on Manifolds, Nice, France, 2017.
Status: Published
V. Naumova and K. Schnass

Dictionary Learning from Incomplete Data for Efficient Image Restoration

In 2017 European Signal Processing Conference, Kos Island, Greece. EURASIP, 2017.
Status: Published