From Stochastic to Deterministic: SGD dynamics of non-convex models in high dimensionsStochastic gradient descent (SGD) stands as a cornerstone of optimization and modern machine learning. However, understanding why SGD performs so well remains a major challenge. In this talk, I will present a theory for SGD in high dimensions when the number of samples and […]