Concepts2

Groups

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