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Search results for biblio_year:1979
Filters: 1 is biblio_year:2001 and 2 is biblio_type:Master's thesis and 3 is biblio_year:2003 and 4 is biblio_year:2004 and 5 is biblio_type:Book and 6 is biblio_year:2018 and 7 is biblio_year:2009 and 8 is biblio_type:Talks, invited and 9 is field_research_area:590 and 10 is biblio_year:2019 and Author is Massimo Fornasier  [Reset Search]
2021
C. Fiedler, M. Fornasier, T. Klock and M. Rauchensteiner. "Stable Recovery of Entangled Weights: Towards Robust Identification of Deep Neural Networks from Minimal Samples." arXiv (2021).
2019
M. Fornasier, E. De Vito, Z. Kereta and V. Naumova. Automated parameter estimation for selected inverse problems In Grenoble, France., 2019.
M. Fornasier, T. Klock and M. Rauchensteiner. Identifying weights of overcomplete shallow- and two layer neural networksusing few network evaluations. Deepmath Conference, New York, USA, 2019.
M. Fornasier, T. Klock and M. Rauchensteiner. "Robust and Resource Efficient Identification of Two Hidden Layer Neural Networks." Constructive Approximation (2019).
2018
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).PDF icon 1801.06240-2.pdf (1.53 MB)
2017
M. Fornasier, J. Maly and V. Naumova. Robust Recovery of Low-Rank Matrices using Multi-Penalty Regularization In NIPS Workshop Optimisation for Machine Learning. Long Beach, USA, 2017.
2016
E. De Vito, M. Fornasier and V. Naumova. "A Machine Learning Approach to Optimal Tikhonov Regularization I." Journal of Machine Learning Research (2016).PDF icon learning_parameter.pdf (472.12 KB)
2014
M. Fornasier, V. Naumova and S. V. Pereverzyev. Multi-Parameter Regularization and High-Dimensional Learning. Savannah, USA: SIAM Uncertainty Quantification, 2014.
V. Naumova, M. Fornasier and S. V. Pereverzyev. "Parameter Choice Strategies for Multi-Penalty Regularization." SIAM Journal on Numerical Analysis 52 (2014): 1770-1794.PDF icon simula.simula.2840.pdf (400.4 KB)