| dc.contributor.author | Cifuentes, Diego | |
| dc.contributor.author | Harris, Corey | |
| dc.contributor.author | Sturmfels, Bernd | |
| dc.date.accessioned | 2021-09-20T17:29:30Z | |
| dc.date.available | 2021-09-20T17:29:30Z | |
| dc.date.issued | 2019-05-15 | |
| dc.identifier.uri | https://hdl.handle.net/1721.1/131668 | |
| dc.description.abstract | Abstract
Consider the problem of minimizing a quadratic objective subject to quadratic equations. We study the semialgebraic region of objective functions for which this problem is solved by its semidefinite relaxation. For the Euclidean distance problem, this is a bundle of spectrahedral shadows surrounding the given variety. We characterize the algebraic boundary of this region and we derive a formula for its degree. | en_US |
| dc.publisher | Springer Berlin Heidelberg | en_US |
| dc.relation.isversionof | https://doi.org/10.1007/s10107-019-01399-8 | en_US |
| dc.rights | Creative Commons Attribution | en_US |
| dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | en_US |
| dc.source | Springer Berlin Heidelberg | en_US |
| dc.title | The geometry of SDP-exactness in quadratic optimization | en_US |
| dc.type | Article | en_US |
| dc.contributor.department | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory | |
| dc.contributor.department | Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science | |
| dc.identifier.mitlicense | PUBLISHER_CC | |
| dc.eprint.version | Final published version | en_US |
| dc.type.uri | http://purl.org/eprint/type/JournalArticle | en_US |
| eprint.status | http://purl.org/eprint/status/PeerReviewed | en_US |
| dc.date.updated | 2020-06-26T12:53:39Z | |
| dc.language.rfc3066 | en | |
| dc.rights.holder | The Author(s) | |
| dspace.embargo.terms | N | |
| dspace.date.submission | 2020-06-26T12:53:39Z | |
| mit.license | PUBLISHER_CC | |
| mit.metadata.status | Authority Work and Publication Information Needed | |
