4 citations · 8 across the 3 of their papers we have counts for
5 papers
Leveraging Christoffel-Darboux Kernels to Strengthen Moment-SOS Relaxations
Srećko Ðurašinović, Perla Azzi, Jean-Bernard Lasserre +3
The classical Moment-Sum Of Squares hierarchy allows to approximate a global minimum of a polynomial optimization problem through semidefinite relaxations of increasing size. Howev…
Rank conditions for exactness of semidefinite relaxations in polynomial optimization
Jean B Lasserre
We consider the Moment-SOS hierarchy in polynomial optimization. We first provide a sufficient condition to solve the truncated K-moment problem associated with a given degree-…
Semialgebraic Representation of Monotone Deep Equilibrium Models and Applications to Certification
Tong Chen, Jean-Bernard Lasserre, Victor Magron +1
Deep equilibrium models are based on implicitly defined functional relations and have shown competitive performance compared with the traditional deep networks. Monotone operator e…
A hierarchy of spectral relaxations for polynomial optimization
Ngoc Hoang Anh Mai, Victor Magron, Jean-Bernard Lasserre
We show that (i) any constrained polynomial optimization problem (POP) has an equivalent formulation on a variety contained in an Euclidean sphere and (ii) the resulting semidefini…
TSSOS: A Moment-SOS hierarchy that exploits term sparsity
Jie Wang, Victor Magron, Jean-Bernard Lasserre
This paper is concerned with polynomial optimization problems. We show how to exploit term (or monomial) sparsity of the input polynomials to obtain a new converging hierarchy of s…