Newton and interior-point methods for (constrained) nonconvex-nonconcave minmax optimization with stability guarantees.
Raphael ChinchillaGuosong YangJoão Pedro HespanhaPublished in: CoRR (2022)
Keyphrases
- interior point methods
- convex optimization
- convex programming
- quadratic programming
- linear program
- lagrange multipliers
- norm minimization
- semidefinite
- linear programming
- nonlinear programming
- interior point
- primal dual
- optimization problems
- global optimization
- semidefinite programming
- convex relaxation
- quadratically constrained quadratic
- solving problems
- linear programming problems
- low rank
- analytic center
- quadratic program
- semi infinite
- extreme points
- objective function
- machine learning
- linear systems
- convex sets
- computationally intensive
- multiple objectives
- dynamic programming
- pairwise
- optimal solution
- image processing