Concepts2
📚TheoryAdvanced
PAC-Bayes Theory
PAC-Bayes provides high-probability generalization bounds for randomized predictors by comparing a data-dependent posterior Q to a fixed, data-independent prior P through KL(Q||P).
#pac-bayes#generalization bound#kl divergence+12
📚TheoryAdvanced
Deep Learning Generalization Theory
Deep learning generalization theory tries to explain why overparameterized networks can fit (interpolate) training data yet still perform well on new data.
#generalization#implicit regularization#minimum norm+12