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Bilevel approaches for learning of variational imaging models
[article]
2015
arXiv
pre-print
We review some recent learning approaches in variational imaging, based on bilevel optimisation, and emphasize the importance of their treatment in function space. The paper covers both analytical and numerical techniques. Analytically, we include results on the existence and structure of minimisers, as well as optimality conditions for their characterisation. Based on this information, Newton type methods are studied for the solution of the problems at hand, combining them with sampling
arXiv:1505.02120v1
fatcat:zbj34jpfsbetxkb2fjc2ef2674