Toward Learning Robust and Invariant Representations with Alignment Regularization and Data Augmentation

Haohan Wang, Zeyi Huang, Xindi Wu +1

Data augmentation has been proven to be an effective technique for developing machine learning models that are robust to known classes of distributional shifts (e.g., rotations of…