Statistical Foundations of Deep Learning

3 credits · Graduate School

Statistical learning theory, parametric learning with high-dimensional data, optimization techniques, a unified view of deep neural architectures and broad overview of learning settings including supervised, unsupervised, self-supervised, meta, continual, and reinforcement learning. Emphasis on mathematical foundations. [3]