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This work proposes a new moment-SOS hierarchy, called CS-TSSOS, for solving large-scale sparse polynomial optimization problems.
Anneaux préordonnés
Jean-Louis Krivine · 1964
Earlier work this paper cites.
Incidence matrices and interval graphs
Delbert Fulkerson and Oliver Gross · 1965
Earlier work this paper cites.
A nullstellensatz and a positivstellensatz in semialgebraic geometry
Gilbert Stengle · 1974
Earlier work this paper cites.
Extremal PSD forms with few terms
Bruce Reznick · 1978
Earlier work this paper cites.
Positive definite completions of partial hermitian matrices
Robert Grone, Charles R. Johnson, Eduardo M. Sá, and Henry Wolkowicz · 1984
Earlier work this paper cites.
Quadratic optimization problems
Naum Z. Shor · 1987
Earlier work this paper cites.
Positive semidefinite matrices with a given sparsity pattern
Jim Agler, William Helton, Scott McCullough, and Leiba Rodman · 1988
Earlier work this paper cites.
An introduction to chordal graphs and clique trees
Jean R. S. Blair and Barry Peyton · 1993
Earlier work this paper cites.
The MOSEK interior point optimizer for linear programming: an implementation of the homogeneous algorithm
Erling D. Andersen and Knud D. Andersen · 2000
Earlier work this paper cites.
Global Optimization with Polynomials and the Problem of Moments
Jean B. Lasserre · 2001
Earlier work this paper cites.
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Monique Laurent · 2003
Earlier work this paper cites.
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Martin Charles Golumbic · 2004
Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
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Earlier work this paper cites.
A note on the representation of positive polynomials with structured sparsity
David Grimm, Tim Netzer, and Markus Schweighofer · 2007
Earlier work this paper cites.
Algorithm 883: SparsePOP—a sparse semidefinite programming relaxation of polynomial optimization problems
Hayato Waki, Sunyoung Kim, Masakazu Kojima, Masakazu Muramatsu, and Hiroshi Sugimoto · 2008
Earlier work this paper cites.
Systems polynomial optimization tools (SPOT), 2010
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Handbook of semidefinite programming: theory, algorithms, and applications
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Anders Eltved, Joachim Dahl, and Martin S. Andersen · 2019
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Jared Miller, Yang Zheng, Mario Sznaier, and Antonis Papachristodoulou · 2019
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A new sparse SOS decomposition algorithm based on term sparsity
Jie Wang, Haokun Li, and Bican Xia · 2019
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Semialgebraic optimization for bounding Lipschitz constants of ReLU networks
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