activity
20152026
most citedTSSOS: a Julia library to exploit sparsity for large-scale polynomial optimization

12 citations · 37 across the 43 of their papers we have counts for

collaborators
Showing math.OCShow all

47 papers · 1 filter

math.OC2026

Sums of squares in polynomial time

Nikolas Gärtner, Victor Magron, Frank Vallentin

In this paper, we analyze the bit complexity of deciding whether a given polynomial can be represented as a sum of squares of polynomials. We show that the weak membership problem…

math.OC2026

Duality attainment and strict feasibility of the generalized moment problem and its relaxations

Sami Halaseh, Victor Magron, Mateusz Skomra

The generalized moment problem (GMP) is an infinite dimensional linear problem over the cone of finite nonnegative Borel measures. When a GMP instance involves finitely many polyno…

math.OC2026

Robust self-testing with CHSH mod 3

Igor Klep, Nando Leijenhorst, Victor Magron

The CHSH mod 3 Bell inequality is a natural testbed for higher-dimensional quantum nonlocality, yet its maximal quantum violation and self-testing properties have remained unresolv…

math.OC2026

The Effective Lasserre's Perturbative Positivstellensatz

Igor Klep, Victor Magron, Matthias Schötz

We study sum-of-squares (SOS) certificates for nonnegative polynomials on and their implications for polynomial optimization over unbounded domains. Building on…

math.OC2025

Finite Convergence of the Moment-SOS Hierarchy on the Product of Spheres

Sami Halaseh, Victor Magron, Mateusz Skomra

We study the polynomial optimization problem of minimizing a multihomogeneous polynomial over the product of spheres. This polynomial optimization problem models the tensor optimiz…

math.OC2025

Exploiting Term Sparsity in Symmetry-Adapted Basis for Polynomial Optimization

Igor Klep, Victor Magron, Tobias Metzlaff +1

Polynomial optimization problems are infinite-dimensional, nonconvex, NP-hard, and are often handled in practice with the moment-sums of squares hierarchy of semidefinite programmi…