Search Results for author: Jean-Bernard Lasserre

Found 10 papers, 6 papers with code

Tractable hierarchies of convex relaxations for polynomial optimization on the nonnegative orthant

no code implementations13 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).

A Sublevel Moment-SOS Hierarchy for Polynomial Optimization

1 code implementation13 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

Chordal-TSSOS: a moment-SOS hierarchy that exploits term sparsity with chordal extension

1 code implementation4 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

Semialgebraic Optimization for Lipschitz Constants of ReLU Networks

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.

Adversarial Robustness

TSSOS: A Moment-SOS hierarchy that exploits term sparsity

3 code implementations18 Dec 2019 Jie Wang, Victor Magron, Jean-Bernard Lasserre

This paper is concerned with polynomial optimization problems.

Optimization and Control

Positivity certificates and polynomial optimization on non-compact semialgebraic sets

2 code implementations26 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

Data analysis from empirical moments and the Christoffel function

no code implementations19 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.

Approximate Optimal Designs for Multivariate Polynomial Regression

1 code implementation9 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)

The empirical Christoffel function with applications in data analysis

no code implementations11 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.

BIG-bench Machine Learning Novelty Detection

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