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2020 – today
- 2022
[j8]Andreas Oslandsbotn, Zeljko Kereta
, Valeriya Naumova, Yoav Freund, Alexander Cloninger:
StreaMRAK a streaming multi-resolution adaptive kernel algorithm. Appl. Math. Comput. 426: 127112 (2022)- [j7]Geir Severin R. E. Langberg, Mikal Stapnes, Jan F. Nygård, Mari Nygård, Markus Grasmair, Valeriya Naumova:
Matrix factorization for the reconstruction of cervical cancer screening histories and prediction of future screening results. BMC Bioinform. 23-S(12): 484 (2022) - 2021
- [j6]Massimo Fornasier, Johannes Maly, Valeriya Naumova:
Robust recovery of low-rank matrices with non-orthogonal sparse decomposition from incomplete measurements. Appl. Math. Comput. 392: 125702 (2021) - [c5]Vinay Chakravarthi Gogineni, Severin R. E. Langberg, Valeriya Naumova, Jan F. Nygård, Mari Nygård, Markus Grasmair, Stefan Werner:
Recurrent Time-Varying Multi-Graph Convolutional Neural Network for Personalized Cervical Cancer Risk Prediction. ACSCC 2021: 1541-1545 - [c4]Vinay Chakravarthi Gogineni, Valeriya Naumova, Stefan Werner, Yih-Fang Huang:
Graph Kernel Recursive Least-Squares Algorithms. APSIPA ASC 2021: 2072-2076 - [c3]Vinay Chakravarthi Gogineni, Severin R. E. Langberg, Valeriya Naumova, Jan F. Nygård, Mari Nygård, Markus Grasmair, Stefan Werner:
Data-Driven Personalized Cervical Cancer Risk Prediction: A Graph-Perspective. SSP 2021: 46-50 - [i6]Andreas Oslandsbotn, Zeljko Kereta, Valeriya Naumova, Yoav Freund, Alexander Cloninger:
SreaMRAK a Streaming Multi-Resolution Adaptive Kernel Algorithm. CoRR abs/2108.10411 (2021)
2010 – 2019
- 2019
- [i5]Zeljko Kereta, Timo Klock, Valeriya Naumova:
Nonlinear generalization of the single index model. CoRR abs/1902.09024 (2019) - [i4]Zeljko Kereta, Johannes Maly, Valeriya Naumova:
Linear convergence and support recovery for non-convex multi-penalty regularization. CoRR abs/1908.02503 (2019) - 2018
- [j5]Valeriya Naumova, Karin Schnass:
Fast dictionary learning from incomplete data. EURASIP J. Adv. Signal Process. 2018: 12 (2018) - [i3]Ernesto De Vito, Zeljko Kereta, Valeria Naumova:
A Learning Theory Approach to a Computationally Efficient Parameter Selection for the Elastic Net. CoRR abs/1809.08696 (2018) - 2017
- [c2]Valeriya Naumova, Karin Schnass:
Dictionary learning from incomplete data for efficient image restoration. EUSIPCO 2017: 1425-1429 - [i2]Valeriya Naumova, Karin Schnass:
Dictionary Learning from Incomplete Data. CoRR abs/1701.03655 (2017) - [i1]Markus Grasmair, Timo Klock, Valeriya Naumova:
Adaptive multi-penalty regularization based on a generalized Lasso path. CoRR abs/1710.03971 (2017) - 2014
- [j4]Massimo Fornasier, Valeriya Naumova, Sergei V. Pereverzyev:
Parameter Choice Strategies for Multipenalty Regularization. SIAM J. Numer. Anal. 52(4): 1770-1794 (2014) - 2013
- [j3]Hrushikesh Narhar Mhaskar, Valeriya Naumova, Sergei V. Pereverzyev:
Filtered Legendre expansion method for numerical differentiation at the boundary point with application to blood glucose predictions. Appl. Math. Comput. 224: 835-847 (2013) - 2012
- [j2]Valeriya Naumova, Sergei V. Pereverzyev, Sivananthan Sivananthan:
Adaptive parameter choice for one-sided finite difference schemes and its application in diabetes technology. J. Complex. 28(5-6): 524-538 (2012) - [j1]Valeriya Naumova, Sergei V. Pereverzyev, Sivananthan Sivananthan:
A meta-learning approach to the regularized learning - Case study: Blood glucose prediction. Neural Networks 33: 181-193 (2012) - 2011
- [c1]Valeriya Naumova, Sergei V. Pereverzyev, Sivananthan Sampath:
Reading blood glucose from subcutaneous electric current by means of a regularization in variable Reproducing Kernel Hilbert Spaces. CDC/ECC 2011: 5158-5163
Coauthor Index
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