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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Factorization norms and an inverse theorem for MaxCut. [PDF]
Balla I, Hambardzumyan L, Tomon I.
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A Variational Formulation for Irreversible Thermodynamics with Path Dependence. [PDF]
Ren H.
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Convergence and stability analysis of the Extended Infinite Horizon Model Predictive Control. [PDF]
Alvarez LA +2 more
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Fast implementation for semidefinite programs with positive matrix completion
identifier:oai:t2r2.star.titech.ac.jp ...
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A Mathematical Analysis of IPT-DMFT. [PDF]
Cancès E, Kirsch A, Perrin-Roussel S.
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Robust Stability and Robust Stabilization of Discrete-Time Markov Jump Linear Systems Under a Class of Stochastic Structured Nonlinear Uncertainties. [PDF]
Dragan V, Aberkane S.
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Movable Antenna-Enabled RIS-Assisted Simultaneous Wireless Information and Power Transfer Systems. [PDF]
Feng D, Zhang X, Yu X, Wang X, Shi X.
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Single-cell 3D genome reconstruction in the haploid setting using rigidity theory. [PDF]
Dewar S +4 more
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