2025
Generalization Guarantees for Representation Learning via Data-Dependent Gaussian Mixture Priors
ICLR 2025spotlight
We establish in-expectation and tail bounds on the generalization error of representation learning type algorithms. The bounds are in terms of the relative entropy between the distribution of the representations extracted from the training and "test'' datasets and a data-dependent symmetric prior, i…