M. Grasmair, T. Klock and V. Naumova. "Adaptive multi-penalty regularization based on a generalized Lasso path." arXiv (2017).

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M. Grasmair, T. Klock and V. Naumova. " Adaptive multi-penalty regularization based on a generalized Lasso path." Applied and Computational Harmonic Analysis (2017).

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arxiv_paper.pdf (1.86 MB)

V. Naumova. Advanced statistics and data analysis for blood glucose prediction and diabetes In Universitäres Herzzentrum Hamburg., 2017.

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V. Naumova and K. Schnass. "Dictionary Learning from Incomplete Data." IEEE Transactions on Signal Processing (2017).

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1701.03655v1.pdf (883.91 KB)

V. Naumova and K. Schnass. Dictionary Learning from Incomplete Data for Efficient Image Restoration In EUSIPCO., 2017.

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bare_conf.pdf (1.24 MB)

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.

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V. Naumova. Image separation using multi-penalty regularization In CEA Saclay, France., 2017.

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V. Naumova. Innovative solution of unmixing problems by means of multi-penalty regularization In Applied Inverse Problems, Hangzhou, China., 2017.

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V. Naumova. A machine learning approach to optimal regularization: affine manifolds In International Workshop Dictionary Learning on Manifolds, Nice, France., 2017.

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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, Edited by T. Klock., 2017.

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K. Hlavackova-Schindler, V. Naumova and S. V. Pereverzyev. "Multi-penalty regularization for detecting relevant variables." In Recent Applications of Harmonic Analysis to Function Spaces, Differential Equations, and Data Science, edited by I. Pesenson. Novel Methods in Harmonic Analysis, ed. Vol. 2. Springer International Publishing, 2017.

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pp_11_2014-1.pdf (390.69 KB)

V. Naumova. A novel approach for prediction of the future blood glucose evolution in a diabetes patient In AFib-TrainNet Status Seminar, Hamburg., 2017.

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B. Leon, V. Naumova, E. Ruiz-Velazquez, A. McCulloch and E. Sanchez. "Combination of Neural Inverse Optimal Control with a Kernel-Based Regularization Learning Algorithm to Prevent Hypoglycemia in Type 1 Diabetes Patients." IEEE Transactions on Neural Networks and Learning Systems (2016).

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ieeetnnls.pdf (369.99 KB)

M. Grasmair and V. Naumova. "Conditions on optimal support recovery in unmixing problems by means of multi-penalty regularization." Inverse Problems 32, no. 10 (2016).

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granau15_final.pdf (332.99 KB)

V. Naumova. Dictionary Learning from Incomplete Data In 2016 SIAM Conference on Imaging Science., 2016.

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V. Naumova. From Big Data to Big Insights In EUMLS Final Conference., 2016.

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V. Naumova. Innovative solution of unmixing problems by means of multi-penalty regularization: theoretical and algorithmical aspects In University of Graz., 2016.

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E. De Vito, M. Fornasier and V. Naumova. "A Machine Learning Approach to Optimal Tikhonov Regularization I." Journal of Machine Learning Research (2016).

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learning_parameter.pdf (472.12 KB)

V. Naumova, L. Nita, J. Poulsen and S. V. Pereverzyev. "Meta-Learning Based Blood Glucose Predictor for Diabetic Smartphone App." In Prediction Methods for Blood Glucose Concentration. Lecture Notes in Bioengineering. , 93-105. Aachen (Germany): Springer International Publishing, 2016.

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V. Naumova, K. Hlavackova-Schindler and S. V. Pereverzyev. "Granger Causality for Ill-Posed Problems: Ideas, Methods, and Application in Life Sciences." In Statistics and Causality: Methods for Applied Empirical Research, edited by W. Wiedermann and A. von Eye, 1-41. West Sussex, United Kingdom: John Wiley & Sons Limited Wiley, 2015.

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V. Naumova. Autumn School on Mathematical Imaging and Statistical Learning In University of Verona., 2014.

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V. Naumova. Meta-Learning Approach to the Image Denoising Problem In SIAM Conference on Imaging Science., 2014.

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V. Naumova. Meta-Learning Based Blood Glucose Predictor for Diabetic Smartphone App In Workshop on Design, use and evaluation of prediction methods for blood glucose concentration., 2014.

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V. Naumova, S. V. Pereverzyev, L. Nita and J. Poulsen. Meta-Learning Based Blood Glucose Predictor for Diabetic Smartphone App., 2014.

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V. Naumova. Minimization of Multi-Penalty Functionals by Alternating Iterative Thresholding and Optimal Parameter Choices In SIAM Conference on Uncertainty Quantification., 2014.

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