Polynomial Optimization via Random Projection and Consensus
Etienne Buehrle, Christoph Stiller
公開日: 2025/9/16
Abstract
We propose a black-box approach to reducing large semidefinite programs to a set of smaller semidefinite programs by projecting to random linear subspaces. We evaluate our method on a set of polynomial optimization problems, demonstrating improved scalability.