Semidefinite relaxation of quadratic optimization problems
Refereed conference paper presented and published in conference proceedings

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AbstractIn recent years, the semidefinite relaxation (SDR) technique has been at the center of some of very exciting developments in the area of signal processing and communications, and it has shown great significance and relevance on a variety of applications. Roughly speaking, SDR is a powerful, computationally efficient approximation technique for a host of very difficult optimization problems. In particular, it can be applied to many nonconvex quadratically constrained quadratic programs (QCQPs) in an almost mechanical fashion, including the following problem: © 2010 IEEE.
All Author(s) ListLuo Z.-Q., Ma W.-K., So A., Ye Y., Zhang S.
Volume Number27
Issue Number3
PublisherInstitute of Electrical and Electronics Engineers
Place of PublicationUnited States
Pages20 - 34
LanguagesEnglish-United Kingdom

Last updated on 2021-17-01 at 01:30