Ekin D. Cubuk

Improving Robustness Without Sacrificing Accuracy with Patch Gaussian Augmentation

2019 · arXiv (Cornell University)

Deploying machine learning systems in the real world requires both high accuracy on clean data and robustness to naturally occurring corruptions. While architectural advances have led to improved accuracy, building robust models remains challenging. Prior …

Tied-Augment: Controlling Representation Similarity Improves Data Augmentation

2023 · arXiv (Cornell University)

Data augmentation methods have played an important role in the recent advance of deep learning models, and have become an indispensable component of state-of-the-art models in semi-supervised, self-supervised, and supervised training for vision. Despite incurring …