arXiv stat.ML
· Papers
Random Matrix Theory for Deep Learning: Beyond Eigenvalues of Linear Models
arXiv:2506.13139v3 Announce Type: replace Abstract: Modern Machine Learning (ML) and Deep Neural Networks (DNNs) often operate on high-dimensional data and rely on overparameterized models, where classical low-dimensional intuitions break down. In particular, the proportional regime where the data dimension, sample siz