A scalable estimator of sets of integral operators

Abstract : The main objective of this work is to estimate a low dimensional subspace of operators in order to improve the identifiability of blind inverse problems. We propose a scalable method to find a subspace $\widehat \H$ of low-rank tensors that simultaneously approximates a set of integral operators. The method can be seen as a generalization of tensor decomposition models, which was never used in this context. In addition, we propose to construct a convex subset of $\widehat \H$ in order to further reduce the search space. We provide theoretical guarantees on the estimators and a few numerical results.
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Contributor : Pierre Weiss <>
Submitted on : Thursday, July 18, 2019 - 11:10:31 AM
Last modification on : Friday, July 19, 2019 - 1:27:32 AM




Valentin Debarnot, Paul Escande, Pierre Weiss. A scalable estimator of sets of integral operators. Inverse Problems, IOP Publishing, 2019, ⟨10.1088/1361-6420/ab2fb3⟩. ⟨hal-02174477⟩



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