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We have seen that under rather natural source condi- tions error estimates in Bregman distances can be extended from the well-known quadratic fitting (Gaussian noise) case to

Mainly, by using the extrapolation method, families of estimates can be derived which are valid for any nonsingular matrix and thus can be used for nonsymmetric problems. In

M AASS , A generalized conditional gradient method for nonlinear operator equations with sparsity constraints, Inverse Problems, 23 (2007), pp.. M AASS , A generalized

In summary, based on the performance of the APBBi methods and Lin’s method on the four types of randomly generated NMF problems using the aforementioned stopping criteria, we

In this paper, we extend the results of [14, 20] to general minimization-based noise level- free parameter choice rules and general spectral filter-based regularization operators..

As an approximation of a fourth order differential operator, the condition number of the discrete problem grows at the rate of h −4 ; cf. Thus a good preconditioner is essential

In this paper we develop and analyze new local convex ap- proximation methods with explicit solutions of non-linear problems for unconstrained op- timization for large-scale systems

(i) the original formulas in terms of infinite products involving reflections of the mapping parameters as first derived by [20] for the annulus, [21] for the unbounded case, and