Noisy Gradient Descent Algorithms

This lecture discusses the motivation behind noisy gradient descent algorithms, their performance compared to message passing and SCPs, and the use of the spiked mixed matrix tensor model to analyze large-scale algorithms. It also covers the Bayesian estimator, approximate message passing, and the Langevin algorithm, exploring their properties and performance in high-dimensional non-convex optimization problems.