- Title
- Maximum entropy and feasibility methods for convex and nonconvex inverse problems
- Creator
- Borwein, Jonathan M.
- Relation
- Optimization Vol. 61, Issue 1, p. 1-33
- Publisher Link
- http://dx.doi.org/10.1080/02331934.2011.632502
- Publisher
- Taylor & Francis
- Resource Type
- journal article
- Date
- 2012
- Description
- We discuss informally two approaches to solving convex and nonconvex feasibility problems – via entropy optimization and via algebraic iterative methods. We shall highlight the advantages and disadvantages of each and give various related applications and limiting examples. While some of the results are very classical, they are not as well-known to practitioners as they should be. A key role is played by the Fenchel conjugate.
- Subject
- entropy optimization; Fenchel duality theorem; inverse problems; feasibility problems; alternating projection and reflection methods
- Identifier
- http://hdl.handle.net/1959.13/940081
- Identifier
- uon:12942
- Identifier
- ISSN:0233-1934
- Rights
- This is an electronic version of an article published in Optimization Vol. 61, Issue 1, p. 1-33. Optimization is available online at: http://www.tandfonline.com/openurl?genre=article&issn=0233-1934&volume=61&issue=1&spage=1
- Language
- eng
- Full Text
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| Thumbnail | File | Description | Size | Format | |||
|---|---|---|---|---|---|---|---|
| View Details Download | ATTACHMENT02 | Author final version | 4 MB | Adobe Acrobat PDF | View Details Download |