Multivariate Polynomial Optimization

SIGNAL ANALYSIS

Machine learning and signal processing rely on universal function approximation. Multivariate polynomial models offer a natural way to express complex input-output relationships. The authors propose (MPO)$^2$, a method for multivariate polynomial optimization based on matrix product operators. This could improve function approximation and learning from limited data. If your model relies on polynomial approximations, you might want to take a closer look.