arXiv stat.ML
· Papers
Informational Frustration in Neural Manifolds: Shannon Bottlenecks and the Limits of Learnability
arXiv:2606.30512v1 Announce Type: cross Abstract: Why overparameterised deep networks generalise so remarkably well remains one of the most stubborn open questions in machine learning theory. Classical frameworks like VC dimension and Rademacher complexity predict catastrophic overfitting in modern models, leaving a ma