Curse of Dimensionality in Deep Learning

This lecture explores the landscape, performance, and curse of dimensionality in deep learning, discussing the challenges of classifying data in large dimensions, the principles of deep learning, the geometry of loss landscape, overfitting phenomena, and the impact of dimensionality on learning. It also delves into the concepts of locality, hierarchy, sparsity, and stability in relation to smooth deformations in neural networks.