Sum-of-squares relaxations for polynomial min-max problems over simple sets

DOI10.1007/S10107-024-02072-5MaRDI QIDQ6665389

Francis Bach

Publication date: 17 January 2025

Published in: Mathematical Programming. Series A. Series B (Search for Journal in Brave)

zbMATH Keywords

semidefinite programmingpolynomial optimizationsum-of-squaresmin-max problems

Mathematics Subject Classification ID

Semidefinite programming (90C22) Sums of squares and representations by other particular quadratic forms (11E25)

Cites Work

• Title not available (Why is that?)
• Title not available (Why is that?)
• Title not available (Why is that?)
• Title not available (Why is that?)
• Title not available (Why is that?)
• Min-max and robust polynomial optimization
• Semidefinite programming for min-max problems and games
• On general minimax theorems
• Multidimensional Jackson theorems
• Semidefinite programming relaxations for semialgebraic problems
• The sum-of-squares hierarchy on the sphere and applications in quantum information theory
• Matrix sum-of-squares relaxations for robust semi-definite programs
• Global optimization with polynomials and the problem of moments
• On the Lasserre Hierarchy of Semidefinite Programming Relaxations of Convex Polynomial Optimization Problems
• Quasi-Random Sequences and Their Discrepancies
• Practical Aspects of the Moreau--Yosida Regularization: Theoretical Preliminaries
• Detecting Global Optimality and Extracting Solutions in GloptiPoly
• An Interior-Point Method for Semidefinite Programming
• The Moment Problem
• The Moment-SOS Hierarchy
• Spherical Harmonics in p Dimensions

This page was built for publication: Sum-of-squares relaxations for polynomial min-max problems over simple sets

Report a bug (only for logged in users!)Click here to report a bug for this page (MaRDI item Q6665389)