Dimension-Free PAC-Bayes Generalization for Deep Neural Networks via Dirichlet Processes
arXiv:2610.21340v1 Announce Type: new Abstract: Classical PAC-Bayesian generalization theory places prior distributions over Euclidean parameter space $\Theta \subseteq \mathbb{R}^D$, causing relative entropy to scale with network dimension $D$. For modern overparameterized neural networks where $D…
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- 2026-10-16 04:00 · arXiv stat.ML
Dimension-Free PAC-Bayes Generalization for Deep Neural Networks via Dirichlet Processes