181 citations · 332 across the 25 of their papers we have counts for
9 papers · 1 filter
Convergence Rates for Lasserre's Upper-Bound Hierarchy on with Gaussian Measure
Sander Gribling, Igor Klep, Poornendu Kumar
We establish quantitative convergence rates for Lasserre's measure-based upper-bound hierarchy on using the standard Gaussian measure as the reference measure. For a…
Squared polynomial approximation kernels for the hypercube: improved error bounds and implications for Lasserre hierarchies
Sander Gribling, Etienne de Klerk, Juan C. Vera
We propose a new family of polynomial approximation kernels for approximating nonnegative polynomials on the hypercube . Our Kernels produce polynomial sums-of-squares of…
Revisiting the convergence rate of the Lasserre hierarchy for polynomial optimization over the hypercube
Sander Gribling, Etienne de Klerk, Juan Vera
We revisit the problem of minimizing a given polynomial on the hypercube . Lasserre's hierarchy (also known as the moment- or sum-of-squares hierarchy) provides a seq…
A note on the computational complexity of the moment-SOS hierarchy for polynomial optimization
Sander Gribling, Sven Polak, Lucas Slot
The moment-sum-of-squares (moment-SOS) hierarchy is one of the most celebrated and widely applied methods for approximating the minimum of an n-variate polynomial over a feasible r…
Mutually unbiased bases: polynomial optimization and symmetry
Sander Gribling, Sven Polak
A set of orthonormal bases of is called mutually unbiased if whenever and are basis vectors in distinct bases. A natural q…
Bounding the separable rank via polynomial optimization
Sander Gribling, Monique Laurent, Andries Steenkamp
We investigate questions related to the set consisting of the linear maps acting on that can be written as a convex combina…
Bounds on entanglement dimensions and quantum graph parameters via noncommutative polynomial optimization
Sander Gribling, David de Laat, Monique Laurent
In this paper we study bipartite quantum correlations using techniques from tracial noncommutative polynomial optimization. We construct a hierarchy of semidefinite programming low…
Lower bounds on matrix factorization ranks via noncommutative polynomial optimization
Sander Gribling, David de Laat, Monique Laurent
We use techniques from (tracial noncommutative) polynomial optimization to formulate hierarchies of semidefinite programming lower bounds on matrix factorization ranks. In particul…
Matrices with high completely positive semidefinite rank
Sander Gribling, David de Laat, Monique Laurent
A real symmetric matrix is completely positive semidefinite if it admits a Gram representation by (Hermitian) positive semidefinite matrices of any size . The smallest such…