Valeriya Naumova
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A meta-learning approach to the regularized learning—Case study: Blood glucose prediction
V Naumova, SV Pereverzyev, S Sivananthan
Neural Networks 33, 181-193, 2012
Assessment of blood glucose predictors: the prediction-error grid analysis
S Sivananthan, V Naumova, CD Man, A Facchinetti, E Renard, C Cobelli, ...
Diabetes technology & therapeutics 13 (8), 787-796, 2011
Parameter choice strategies for multipenalty regularization
M Fornasier, V Naumova, SV Pereverzyev
SIAM Journal on Numerical Analysis 52 (4), 1770-1794, 2014
Multi-penalty regularization with a component-wise penalization
V Naumova, SV Pereverzyev
Inverse Problems 29 (7), 075002, 2013
Extrapolation in variable RKHSs with application to the blood glucose reading
V Naumova, SV Pereverzyev, S Sivananthan
Inverse Problems 27 (7), 075010, 2011
Minimization of multi-penalty functionals by alternating iterative thresholding and optimal parameter choices
V Naumova, S Peter
Inverse Problems 30 (12), 125003, 2014
Legendre polynomials as a recommended basis for numerical differentiation in the presence of stochastic white noise
S Lu, V Naumova, SV Pereverzev
Journal of Inverse and Ill-posed Problems 21 (2), 193-216, 2013
Filtered Legendre expansion method for numerical differentiation at the boundary point with application to blood glucose predictions
HN Mhaskar, V Naumova, SV Pereverzyev
Applied Mathematics and Computation 224, 835-847, 2013
Dictionary learning from incomplete data for efficient image restoration
V Naumova, K Schnass
2017 25th European Signal Processing Conference (EUSIPCO), 1425-1429, 2017
Fast dictionary learning from incomplete data
V Naumova, K Schnass
EURASIP journal on advances in signal processing 2018 (1), 1-21, 2018
Conditions on optimal support recovery in unmixing problems by means of multi-penalty regularization
M Grasmair, V Naumova
Inverse Problems 32 (10), 104007, 2016
Adaptive parameter choice for one-sided finite difference schemes and its application in diabetes technology
V Naumova, SV Pereverzyev, S Sivananthan
Journal of Complexity 28 (5-6), 524-538, 2012
A machine learning approach to optimal tikhonov regularisation I: Affine manifolds
E De Vito, M Fornasier, V Naumova
arXiv preprint arXiv:1610.01952, 2016
Meta-learning based blood glucose predictor for diabetic smartphone app
V Naumova, L Nita, JU Poulsen, SV Pereverzyev
Prediction methods for blood glucose concentration, 93-105, 2016
Regularized collocation for spherical harmonics gravitational field modeling
V Naumova, SV Pereverzyev, P Tkachenko
GEM-International Journal on Geomathematics 5 (1), 81-98, 2014
Nationwide rollout reveals efficacy of epidemic control through digital contact tracing
A Elmokashfi, J Sundnes, A Kvalbein, V Naumova, SA Reinemo, ...
Nature communications 12 (1), 1-8, 2021
Adaptive multi-penalty regularization based on a generalized lasso path
M Grasmair, T Klock, V Naumova
Applied and Computational Harmonic Analysis 49 (1), 30-55, 2020
Dictionary learning from incomplete data
V Naumova, K Schnass
arXiv preprint arXiv:1701.03655, 2017
Multi-penalty regularization for detecting relevant variables
K Hlaváčková-Schindler, V Naumova, S Pereverzyev
Recent applications of harmonic analysis to function spaces, differential …, 2017
Data-driven personalized cervical cancer risk prediction: A graph-perspective
VC Gogineni, SRE Langberg, V Naumova, JF Nygård, M Nygård, ...
2021 IEEE Statistical Signal Processing Workshop (SSP), 46-50, 2021
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