Research Data Supporting "Learning Filter Functions in Regularisers by Minimising Quotients"
Citation
Benning, M., Gilboa, G., Grah, J. S., & Schönlieb, C. (2017). Research Data Supporting "Learning Filter Functions in Regularisers by Minimising Quotients" [Dataset]. https://doi.org/10.17863/CAM.8419
Description
This data contains the code and images necessary to reproduce the computational results published in "Learning Filter Functions in Regularisers by Minimising Quotients".
Format
MATLAB® R2016b (https://uk.mathworks.com/products/matlab.html), CVX Software for Disciplined Convex Programming (http://cvxr.com/cvx/)
Keywords
Regularisation Learning, Non-linear Eigenproblem, Sparse Regularisation, Generalised Inverse Power Method
Relationships
Publication Reference: https://scirate.com/arxiv/1704.00989
Sponsorship
Isaac Newton Trust (1608(aj))
Leverhulme Trust (ECF-2016-611)
Identifiers
This record's DOI: https://doi.org/10.17863/CAM.8419
Rights
Attribution-ShareAlike 4.0 International, Attribution-ShareAlike 4.0 International, Attribution-ShareAlike 4.0 International, Attribution-ShareAlike 4.0 International, Attribution-ShareAlike 4.0 International, Attribution-ShareAlike 4.0 International, Attribution-ShareAlike 4.0 International, Attribution-ShareAlike 4.0 International, Attribution-ShareAlike 4.0 International
Licence URL: http://creativecommons.org/licenses/by-sa/4.0/http://creativecommons.org/licenses/by-sa/4.0/http://creativecommons.org/licenses/by-sa/4.0/http://creativecommons.org/licenses/by-sa/4.0/http://creativecommons.org/licenses/by-sa/4.0/http://creativecommons.org/licenses/by-sa/4.0/http://creativecommons.org/licenses/by-sa/4.0/http://creativecommons.org/licenses/by-sa/4.0/http://creativecommons.org/licenses/by-sa/4.0/