Complexity of Finding Local Minima in Continuous Optimization

Explore the complexity of finding local minima in continuous optimization problems through this distinguished seminar featuring Amirali Ahmadi from Princeton University. Delve into the intricacies of polynomial optimization, uncovering the challenges in unconstrained and constrained cases. Learn about the NP-hardness of finding critical points for cubic polynomials and the equivalence of finding local minima to semidefinite programming. Discover groundbreaking results on the impossibility of efficient algorithms for finding local minima of quadratic polynomials over polytopes. Gain insights from Ahmadi's extensive research background and numerous accolades in optimization theory, computational dynamical systems, and control-oriented learning.

Distinguished Seminar in Optimization and Data: Amirali Ahmadi (Princeton University)