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A convex analysis approach to iterative regularization methods Leitao, Antonio
Description
We address two well known iterative regularization methods for ill-posed problems (Landweber and iterated-Tikhonov methods) and discuss how to improve the performance of these classical methods by using convex analysis tools. The talk is based on two recent articles (2018): Range-relaxed criteria for choosing the Lagrange multipliers in nonstationary iterated Tikhonov method (with R.Boiger, B.F.Svaiter), and On a family of gradient type projection methods for nonlinear ill-posed problems (with B.F.Svaiter)
Item Metadata
Title |
A convex analysis approach to iterative regularization methods
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Creator | |
Publisher |
Banff International Research Station for Mathematical Innovation and Discovery
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Date Issued |
2019-06-25T16:21
|
Description |
We address two well known iterative regularization methods for
ill-posed problems (Landweber and iterated-Tikhonov methods)
and discuss how to improve the performance of these classical
methods by using convex analysis tools.
The talk is based on two recent articles (2018):
Range-relaxed criteria for choosing the Lagrange multipliers in
nonstationary iterated Tikhonov method (with R.Boiger, B.F.Svaiter),
and
On a family of gradient type projection methods for nonlinear
ill-posed problems (with B.F.Svaiter)
|
Extent |
40.0 minutes
|
Subject | |
Type | |
File Format |
video/mp4
|
Language |
eng
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Notes |
Author affiliation: University of Floranopolis
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Series | |
Date Available |
2019-12-23
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Provider |
Vancouver : University of British Columbia Library
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Rights |
Attribution-NonCommercial-NoDerivatives 4.0 International
|
DOI |
10.14288/1.0387282
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URI | |
Affiliation | |
Peer Review Status |
Unreviewed
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Scholarly Level |
Faculty
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Rights URI | |
Aggregated Source Repository |
DSpace
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Item Media
Item Citations and Data
Rights
Attribution-NonCommercial-NoDerivatives 4.0 International