Results 21 to 30 of about 6,028,400 (221)
Invariant Semidefinite Programs [PDF]
, 2011 In the last years many results in the area of semidefinite programming were obtained for invariant (finite dimensional, or infinite dimensional) semidefinite programs - SDPs which have symmetry. This was done for a variety of problems and applications. The purpose of this handbook chapter is to give the reader the necessary background for dealing with ...
Bachoc, C. +3 more
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Open Journal of Mathematical Optimization, 2022 We address the issue of computing a global minimizer of the AC Optimal Power Flow problem. We introduce valid inequalities to strengthen the Semidefinite Programming relaxation, yielding a novel Conic Programming relaxation.
Oustry, Antoine
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A superlinearly convergent SSDP algorithm for nonlinear semidefinite programming
Journal of Inequalities and Applications, 2019 In this paper, we present a sequential semidefinite programming (SSDP) algorithm for nonlinear semidefinite programming. At each iteration, a linear semidefinite programming subproblem and a modified quadratic semidefinite programming subproblem are ...
Jian Ling Li, Hui Zhang
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Entropy-Penalized Semidefinite Programming [PDF]
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019 Low-rank methods for semi-definite programming (SDP) have gained a lot of interest recently, especially in machine learning applications. Their analysis often involves determinant-based or Schatten-norm penalties, which are difficult to implement in practice due to high computational efforts.
Krechetov, Mikhail +3 more
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A stabilized sequential quadratic semidefinite programming method for degenerate nonlinear semidefinite programs [PDF]
Computational optimization and applications, 2019 In this paper, we propose a new sequential quadratic semidefinite programming (SQSDP) method for solving degenerate nonlinear semidefinite programs (NSDPs), in which we produce iteration points by solving a sequence of stabilized quadratic semidefinite ...
Yuya Yamakawa, Takayuki Okuno
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Quantum Goemans-Williamson Algorithm with the Hadamard Test and Approximate Amplitude Constraints [PDF]
Quantum, 2023 Semidefinite programs are optimization methods with a wide array of applications, such as approximating difficult combinatorial problems. One such semidefinite program is the Goemans-Williamson algorithm, a popular integer relaxation technique.
Taylor L. Patti +3 more
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SDPNAL+: A Matlab software for semidefinite programming with bound constraints (version 1.0) [PDF]
Optim. Methods Softw., 2017 Sdpnal+ is a MATLAB software package that implements an augmented Lagrangian based method to solve large scale semidefinite programming problems with bound constraints.
Defeng Sun +3 more
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Efficient Semidefinite Programming with Approximate ADMM [PDF]
Journal of Optimization Theory and Applications, 2021 AbstractTenfold improvements in computation speed can be brought to the alternating direction method of multipliers (ADMM) for Semidefinite Programming with virtually no decrease in robustness and provable convergence simply by projecting approximately to the Semidefinite cone.
Rontsis, N, Goulart, P, Nakatsukasa, Y
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A Customized ADMM Approach for Large-Scale Nonconvex Semidefinite Programming
Mathematics, 2023 We investigate a class of challenging general semidefinite programming problems with extra nonconvex constraints such as matrix rank constraints. This problem has extensive applications, including combinatorial graph problems, such as MAX-CUT and ...
Chuangchuang Sun
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Semidefinite programming hierarchies for constrained bilinear optimization [PDF]
Mathematical programming, 2018 We give asymptotically converging semidefinite programming hierarchies of outer bounds on bilinear programs of the form Tr[H(D⊗E)]\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb ...
M. Berta +3 more
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