P. M. Florvaag, V. Naumova and K. Valen-Sendstad. AUTOMATED AND OBJECTIVE SEGMENTATION OF MEDICAL IMAGES USING MACHINE LEARNING TECHNIQUES: ALL MODELS ARE WRONG, BUT SOME ARE USEFUL In Computational and Mathematical Biomedical Engineering. Sendai, Japan: 6th International Conference on Computational & Mathematical Biomedical Engineering (CMBE19), 2019.

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no_pdf_yet.docx (21.56 KB)

M. Fornasier, E. De Vito, Z. Kereta and V. Naumova. Automated parameter estimation for selected inverse problems In Grenoble, France., 2019.

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P. M. Florvaag, V. Strøm, C. Glinge, R. Jabbari, N. Vejlstrup, T. Engstrom, K. A. Ahtarovski, T. Jespersen, J. Tfelt-Hansen, V. Naumova et al. A Combined In-Silico and Machine Learning Approach towards Predicting Arrhythmic Risk in Post-Infarction Patients In Computing in Cardiology, Singapore., 2019.

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Z. Kereta, T. Klock and V. Naumova. Covariance and precision matrix estimation, and dimension reduction in regression problems In Oslo., 2019.

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Z. Kereta, J. Maly and V. Naumova. "Linear convergence and support recovery for non-convex multi-penalty regularization." IEEE TRANSACTIONS ON SIGNAL PROCESSING (2019).

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Z. Kereta, V. Naumova and J. Maly. Linear convergence and support recovery for non-convex multi-penalty regularization In SPARS 2019. Toulouse (France),, 2019.

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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.

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Z. Kereta, T. Klock and V. Naumova. "Nonlinear generalization of the monotone single index model." submitted to Information and Inference (2019).

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Z. Kereta, T. Klock and V. Naumova. Towards nonlinear sufficient dimension reduction In AIP conference, Grenoble., 2019.

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E. De Vito, Z. Kereta and V. Naumova. "Unsupervised parameter selection for denoising with the elastic net." Machine Learning (2019).

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E. De Vito, Z. Kereta and V. Naumova. Unsupervised Parameter Selection in Variational Regularization In SPARS 2019. Toulouse, France, 2019.

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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 (2018).

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arxiv_paper.pdf (1.86 MB)

M. Fornasier, J. Maly and V. Naumova. "A-T-LAS2,1: A Multi-Penalty Approach to Compressed Sensing of Low-Rank Matrices with Sparse Decompositions." IEEE Transactions on Information Theory (2018).

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1801.06240-2.pdf (1.53 MB)

V. Naumova and K. Schnass. "Fast Dictionary Learning from Incomplete Data." EURASIP Journal on Advances in Signal Processing 2018, no. 1 (2018): 12.

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naumova_et_al-2018-eurasip_journal_on_advances_in_signal_processing.pdf (2.27 MB)

Z. Kereta, T. Klock and V. Naumova. A geometrical approach for nonlinear single-index model estimation. ICML Workshop Stockholm, 2018.

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Z. Kereta, T. Klock and V. Naumova. High-dimensional function learning on curves. Cambridge, UK, 2018.

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Z. Kereta, T. Klock and V. Naumova. Inference and estimation for nonlinear single index models. Machine Learning Summer School Spain, 2018.

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E. De Vito, Z. Kereta and V. Naumova. "A Learning Theory Approach to a Computationally Efficient Parameter Selection for the Elastic Net." arXiv (2018).

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1809.08696.pdf (1.75 MB)

V. Naumova and Z. Kereta. A machine learning approach for adaptive parameter selection In University of Oslo, Norway., 2018.

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V. Naumova and Z. Kereta. A machine learning approach to optimal regularization In European Women in Mathematics, Graz, Austria., 2018.

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V. Naumova and Z. Kereta. A machine learning approach to optimal regularization: Affine Manifolds In NTNU, Norway., 2018.

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ntnu.pdf (2.91 MB)

V. Naumova and T. Klock. Multi-parameter regularization for solving inverse problems of unmixing type In University of Cambridge, UK., 2018.

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naumovapresentation1.pdf (2.39 MB)

Z. Kereta, T. Klock and V. Naumova. Nonlinear estimation of single index models In Nonlinear Data: Theory and Algorithms Oberwolfach., 2018.

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

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

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