On Positiveness of Matrix-Valued Polynomials and Robust Semidefinite Programming
This report is devoted to the study of robust semidefinite programming. We show that to the issue of computing the worst-case optimal value of semidefinite programs depending polynomially upon a finite number of bounded scalar parameters, one may associate a countable family of standard semidefinite programs, whose optimal values converge monotonically
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Mobility-Aware ISAC-Assisted Cooperative Jamming for Secure Vehicular URLLC. [PDF]
Michailidis ET +2 more
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Data-driven p-norms for estimating transmission loss coefficients in power systems. [PDF]
Montoya OD +2 more
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Two datasets are better than one: method of double moments for 3D reconstruction in cryo-EM. [PDF]
Kileel J, Mickelin O, Singer A, Xu S.
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Rescaling and Asymptotic Acceleration in Unconstrained Quadratic Optimisation. [PDF]
Zverovich A, Hutchings M, Gauthier B.
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Generalizations of the quadratic bound optimization principle. [PDF]
Li XJ, Tian GL, Zhou H, Lange K.
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Joint Beamforming for Integrated Satellite-Terrestrial ISAC Systems. [PDF]
Wang T, Wang Q.
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Wigner Distribution Sets Universal Lower Bound for Quantum Advantage in Gaussian Boson Sampling. [PDF]
Kocharovsky VV, Kalra K.
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Toeplitz-Enhanced Array Covariance Processing for DOA Estimation Under Low SNR and Limited Snapshots. [PDF]
Jin X +6 more
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