2011
DOI: 10.1007/s10898-011-9715-0
|View full text |Cite
|
Sign up to set email alerts
|

Stability properties of the Tikhonov regularization for nonmonotone inclusions

Abstract: We study the Tikhonov regularization for perturbed inclusions of the form T (x) y * where T is a set-valued mapping defined on a Banach space that enjoys metric regularity properties and y * is an element near 0. We investigate the case when T is metrically regular and strongly regular and we show the existence of both a solution x * to the perturbed inclusion and a Tikhonov sequence which converges to x * . Finally, we show that the Tikhonov sequences associated to the perturbed problem inherit the regularity… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
2
1

Citation Types

0
7
0

Year Published

2011
2011
2021
2021

Publication Types

Select...
3

Relationship

1
2

Authors

Journals

citations
Cited by 3 publications
(7 citation statements)
references
References 13 publications
0
7
0
Order By: Relevance
“…We also present another result, Theorem 3.2, regarding the existence of a (super)linearly convergent proximal point sequence under metric regularity of T , which not only improves both [1, Theorem 3.1] and [2, Theorem 3.2], but is also essential for proving the main theorems. Finally, in the same way as in [10,11], it may be interesting to note that such results show in particular (in a certain perspective), that the proximal method is really wellposed since actually the whole proximal iterates of the problem depend continuously on the data of the problem. The results presented are theoretical; we are interested in studying how the regularity properties (and moduli) carry away from the mapping T to the set of convergent proximal point sequences, and vice versa.…”
Section: Introductionmentioning
confidence: 68%
“…We also present another result, Theorem 3.2, regarding the existence of a (super)linearly convergent proximal point sequence under metric regularity of T , which not only improves both [1, Theorem 3.1] and [2, Theorem 3.2], but is also essential for proving the main theorems. Finally, in the same way as in [10,11], it may be interesting to note that such results show in particular (in a certain perspective), that the proximal method is really wellposed since actually the whole proximal iterates of the problem depend continuously on the data of the problem. The results presented are theoretical; we are interested in studying how the regularity properties (and moduli) carry away from the mapping T to the set of convergent proximal point sequences, and vice versa.…”
Section: Introductionmentioning
confidence: 68%
“…We now briefly discuss how we can use some popular nonsmooth optimisation methods to construct x δ satisfying the accuracy estimate [13] and the parameter convergence conditions [19]. We start with forward-backward splitting, mainly applicable to the 1 -regularised regression of theorem 4.5, in which case it is also known as iterative soft-thresholding [30][31][32].…”
Section: Regularisation Complexity Of Optimisation Methods In Hilbert...mentioning
confidence: 99%
“…Proof. We use corollary 3.7, for which we need to verify [19] for some e δ satisfying [13]. Assumption 3.5 and [12] of assumption 3.1 we have assumed.…”
Section: Regularisation Complexity Of Optimisation Methods In Hilbert...mentioning
confidence: 99%
See 2 more Smart Citations