Complexity aspects of local minima and related notions
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Abstract (arXiv)
We consider the notions of (i) critical points, (ii) second-order points, (iii) local minima, and (iv) strict local minima for multivariate polynomials. For each type of point, and as a function of the degree of the polynomial, we study the complexity of deciding (1) if a given point is of that type, and (2) if a polynomial has a point of that type. Our results characterize the complexity of these two questions for all degrees left open by prior literature. Our main contributions reveal that many of these questions turn out to be tractable for cubic polynomials. In particular, we present an efficiently-checkable necessary and sufficient condition for local minimality of a point for a cubic polynomial. We also show that a local minimum of a cubic polynomial can be efficiently found by solving semidefinite programs of size linear in the number of variables. By contrast, we show that it is strongly NP-hard to decide if a cubic polynomial has a critical point. We also prove that the set of second-order points of any cubic polynomial is a spectrahedron, and conversely that any spectrahedron is the projection of the set of second-order points of a cubic polynomial. In our final section, we briefly present a potential application of finding local minima of cubic polynomials to the design of a third-order Newton method.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 14 Aug 2020.
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Citing papers per year: 2023: 2; 2024: 0; 2025: 0; 2026: 2.
4 papers.
- 2023Symmetry & Critical Points for Symmetric Tensor Decomposition Problemscited by 3
- 2023Higher-Order Newton Methods with Polynomial Work per Iterationcited by 3
- 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
- 2023Higher-Order Newton Methods with Polynomial Work per Iteration10 Nov 2023
- 2023Symmetry & Critical Points for Symmetric Tensor Decomposition Problems13 Jun 2023