Domain Generalization by Mutual-Information Regularization with Pre-trained Models. (arXiv:2203.10789v2 [cs.LG] UPDATED)

Domain generalization (DG) aims to learn a generalized model to an unseen
target domain using only limited source domains. Previous attempts to DG fail
to learn domain-invariant representations only from the source domains due to
the significant domain shifts between training and test domains. Instead, we
re-formulate the DG objective using mutual information with the oracle model, a
model generalized to any possible domain. We derive a tractable variational
lower bound via approximating the oracle model by a pre-trained model, …

arxiv information lg mutual-information pre-trained models regularization