no code implementations • 13 Sep 2022 • Ngoc Hoang Anh Mai, Victor Magron, Jean-Bernard Lasserre, Kim-Chuan Toh
We consider polynomial optimization problems (POP) on a semialgebraic set contained in the nonnegative orthant (every POP on a compact set can be put in this format by a simple translation of the origin).
1 code implementation • 13 Jan 2021 • Tong Chen, Jean-Bernard Lasserre, Victor Magron, Edouard Pauwels
We introduce a sublevel Moment-SOS hierarchy where each SDP relaxation can be viewed as an intermediate (or interpolation) between the d-th and (d+1)-th order SDP relaxations of the Moment-SOS hierarchy (dense or sparse version).
Combinatorial Optimization Optimization and Control
1 code implementation • 4 Mar 2020 • Jie Wang, Victor Magron, Jean-Bernard Lasserre
The novelty and distinguishing feature of such relaxations is to obtain quasi block-diagonal matrices obtained in an iterative procedure that performs chordal extension of certain adjacency graphs.
Optimization and Control 14P10, 90C25, 12D15, 12Y05
2 code implementations • NeurIPS 2020 • Tong Chen, Jean-Bernard Lasserre, Victor Magron, Edouard Pauwels
The Lipschitz constant of a network plays an important role in many applications of deep learning, such as robustness certification and Wasserstein Generative Adversarial Network.
3 code implementations • 18 Dec 2019 • Jie Wang, Victor Magron, Jean-Bernard Lasserre
This paper is concerned with polynomial optimization problems.
Optimization and Control
2 code implementations • 26 Nov 2019 • Ngoc Hoang Anh Mai, Jean-Bernard Lasserre, Victor Magron
As a consequence, it allows one to define a hierarchy of semidefinite relaxations for a general polynomial optimization problem.
Optimization and Control
no code implementations • 19 Oct 2018 • Edouard Pauwels, Mihai Putinar, Jean-Bernard Lasserre
Spectral features of the empirical moment matrix constitute a resourceful tool for unveiling properties of a cloud of points, among which, density, support and latent structures.
1 code implementation • 9 Jun 2017 • Yohann De Castro, Fabrice Gamboa, Didier Henrion, Roxana Hess, Jean-Bernard Lasserre
We introduce a new approach aiming at computing approximate optimal designs for multivariate polynomial regressions on compact (semi-algebraic) design spaces.
Statistics Theory Information Theory Information Theory Numerical Analysis Computation Methodology Statistics Theory 62K05, 90C25 (Primary) 41A10, 49M29, 90C90, 15A15 (secondary)
no code implementations • 11 Jan 2017 • Jean-Bernard Lasserre, Edouard Pauwels
Secondly, we provide a consistency result which relates the empirical Christoffel function and its population counterpart in the limit of large samples.
no code implementations • NeurIPS 2016 • Jean-Bernard Lasserre, Edouard Pauwels
In fact, this SOS polynomial is directly related to orthogonal polynomials and the Christoffel function.