On the complexity of finding a local minimizer of a quadratic function over a polytope
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Abstract (arXiv)
We show that unless P=NP, there cannot be a polynomial-time algorithm that finds a point within Euclidean distance cn (for any constant c ≥ 0) of a local minimizer of an n-variate quadratic function over a polytope. This result (even with c=0) answers a question of Pardalos and Vavasis that appeared in 1992 on a list of seven open problems in complexity theory for numerical optimization. Our proof technique also implies that the problem of deciding whether a quadratic function has a local minimizer over an (unbounded) polyhedron, and that of deciding if a quartic polynomial has a local minimizer are NP-hard.
Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). First posted on arXiv 12 Aug 2020.
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Citing papers per year: 2023: 2; 2024: 1; 2025: 2; 2026: 2.
7 papers.
- 2025SoS1: O1 and R1-Like Reasoning LLMs are Sum-of-Square Solverscited by 5
- 2023Higher-Order Newton Methods with Polynomial Work per Iterationcited by 3
- 2023Testing Stationarity Concepts for ReLU Networks: Hardness, Regularity, and Robust Algorithmscited by 2
- 2024On the Hardness of Meaningful Local Guarantees in Nonsmooth Nonconvex Optimizationcited by 0
- 2025Adaptive Conditional Gradient Descentcited by 0
- 2026On Approximate Computation of Critical Pointscited by 0
- 2026Parameterized Complexity of Stationarity Testing for Piecewise-Affine Functions and Shallow CNN Lossescited by 0
- 2026Parameterized Complexity of Stationarity Testing for Piecewise-Affine Functions and Shallow CNN Losses11 May 2026
- 2026On Approximate Computation of Critical Points29 Jan 2026
- 2025Adaptive Conditional Gradient Descent13 Oct 2025
- 2025SoS1: O1 and R1-Like Reasoning LLMs are Sum-of-Square Solvers27 Feb 2025
- 2024On the Hardness of Meaningful Local Guarantees in Nonsmooth Nonconvex Optimization16 Sep 2024
- 2023Higher-Order Newton Methods with Polynomial Work per Iteration10 Nov 2023
- 2023Testing Stationarity Concepts for ReLU Networks: Hardness, Regularity, and Robust Algorithms23 Feb 2023