2 papers
cs.LG2026
Principles and Practice of Deep Representation Learning: or a Mathematical Theory of Memory
Sam Buchanan, Druv Pai, Peng Wang +1
In the current era of deep learning and especially generative models, there is significant investment in training very large deep neural networks. Thus far, such models have been "…
cs.LG2025
Linearly Separable Features in Shallow Nonlinear Networks: Width Scales Polynomially with Intrinsic Data Dimension
Alec S. Xu, Can Yaras, Peng Wang +1
Deep neural networks have attained remarkable success across diverse classification tasks. Recent empirical studies have shown that deep networks learn features that are linearly s…