We refer to the framework of learning with mixed hard/soft pointwise constraints considered in Gnecco et al., IEEE TNNLS, vol. 26, pp. 2019-2032, 2015. We show that the optimal solution to the learn- ing problem with hard bilateral and linear pointwise constraints stated therein can be obtained as the limit of the sequence of optimal solutions to the related learning problems with soft bilateral and linear pointwise constraints, when the penalty parameter tends to infinity.
Gnecco, G., Gori, M., Melacci, S., Sanguineti, M. (2016). Learning with hard constraints as a limit case of learning with soft constraints. In ESANN 2016 - 24th European Symposium on Artificial Neural Networks (pp.35-40). i6doc.com publication.
Learning with hard constraints as a limit case of learning with soft constraints
Gori, Marco;Melacci, Stefano;
2016-01-01
Abstract
We refer to the framework of learning with mixed hard/soft pointwise constraints considered in Gnecco et al., IEEE TNNLS, vol. 26, pp. 2019-2032, 2015. We show that the optimal solution to the learn- ing problem with hard bilateral and linear pointwise constraints stated therein can be obtained as the limit of the sequence of optimal solutions to the related learning problems with soft bilateral and linear pointwise constraints, when the penalty parameter tends to infinity.File | Dimensione | Formato | |
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https://hdl.handle.net/11365/995426