Jump to navigation

Home

By thinking constantly about it…

Search form

  • Research
  • Education
  • Innovation
  • Home
  • About Simula
  • Publications
  • People
  • Careers
  • Contact
Export 7 results:
  • BibTeX
Filters: Author is Ernesto De Vito  [Clear All Filters]
2020
E. De Vito, M. Fornasier and V. Naumova. "A machine learning approach to optimal Tikhonov regularization I: Affine manifolds." Analysis and Applications (2020).
  • Google Scholar
  • BibTeX
PDF icon learning_parameter.pdf (472.12 KB)
2019
M. Fornasier, E. De Vito, Z. Kereta and V. Naumova. Automated parameter estimation for selected inverse problems In Grenoble, France., 2019.
  • Google Scholar
  • BibTeX
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.
  • Google Scholar
  • BibTeX
E. De Vito, Z. Kereta and V. Naumova. "Unsupervised parameter selection for denoising with the elastic net." Machine Learning (2019).
  • Google Scholar
  • BibTeX
E. De Vito, Z. Kereta and V. Naumova. Unsupervised Parameter Selection in Variational Regularization. SPARS 2019, Toulouse, France, 2019.
  • Google Scholar
  • BibTeX
2018
E. De Vito, Z. Kereta and V. Naumova. "A Learning Theory Approach to a Computationally Efficient Parameter Selection for the Elastic Net." arXiv (2018).
  • Google Scholar
  • BibTeX
PDF icon 1809.08696.pdf (1.75 MB)
2017
E. De Vito, Z. Kereta and V. Naumova. Nearly Optimal Parameter selection for the Elastic Net In Hangzhou, China., 2017.
  • Google Scholar
  • BibTeX

Contacts

Simula Research Laboratory

Kristian Augusts gate 23
0164 Oslo

 

Simula Metropolitan

Pilestredet 52
0167 Oslo

Simula UiB

Thormøhlens gate 53D
5006 Bergen

E-Mail

post@simula.no 

Keep in touch

Facebook LinkedIn Twitter