On optimal low-rank approximation of non-negative matrices
(2015) 54th IEEE Conference on Decision and Control, CDC 2015 p.5278-5283- Abstract
For low-rank Frobenius-norm approximations of matrices with non-negative entries, it is shown that the Lagrange dual is computable by semi-definite programming. Under certain assumptions the duality gap is zero. Even when the duality gap is non-zero, several new insights are provided.
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/51e2b831-b638-4d1f-8028-ab1c5f5c703c
- author
- Grussler, Christian LU and Rantzer, Anders LU
- organization
- publishing date
- 2015
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- Computational modeling, Conferences, Context, Convex functions, Image analysis, Programming, Standards
- host publication
- 2015 IEEE 54th Annual Conference on Decision and Control (CDC)
- pages
- 6 pages
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- conference name
- 54th IEEE Conference on Decision and Control, CDC 2015
- conference location
- Osaka, Japan
- conference dates
- 2015-12-15 - 2015-12-18
- external identifiers
-
- scopus:84962037361
- ISBN
- 978-1-4799-7886-1
- DOI
- 10.1109/CDC.2015.7403045
- language
- English
- LU publication?
- yes
- id
- 51e2b831-b638-4d1f-8028-ab1c5f5c703c
- date added to LUP
- 2016-06-28 12:23:42
- date last changed
- 2023-10-24 01:38:52
@inproceedings{51e2b831-b638-4d1f-8028-ab1c5f5c703c, abstract = {{<p>For low-rank Frobenius-norm approximations of matrices with non-negative entries, it is shown that the Lagrange dual is computable by semi-definite programming. Under certain assumptions the duality gap is zero. Even when the duality gap is non-zero, several new insights are provided.</p>}}, author = {{Grussler, Christian and Rantzer, Anders}}, booktitle = {{2015 IEEE 54th Annual Conference on Decision and Control (CDC)}}, isbn = {{978-1-4799-7886-1}}, keywords = {{Computational modeling; Conferences; Context; Convex functions; Image analysis; Programming; Standards}}, language = {{eng}}, pages = {{5278--5283}}, publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}}, title = {{On optimal low-rank approximation of non-negative matrices}}, url = {{https://lup.lub.lu.se/search/files/21812505/2015cdcGrusslerRantzer.pdf}}, doi = {{10.1109/CDC.2015.7403045}}, year = {{2015}}, }