Relaxed Gauss-Newton methods with applications to electrical impedance tomography
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As second-order methods, Gauss–Newton-type methods can be more effective than first-order methods for the solution of nonsmooth optimization problems with expensive-to-evaluate smooth components. Such methods, however, often do not converge. Motivated by nonlinear inverse problems with nonsmooth regularization, we propose a new Gauss–Newton-type method with inexact relaxed steps. We prove that the method converges to a set of connected critical points given that the linearisation of the forward operator for the inverse problem is sufficiently precise. We extensively evaluate the performance of the method on electrical impedance tomography (EIT).
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