Yian Zhu

$i$-Mix: A Domain-Agnostic Strategy for Contrastive Representation Learning

Contrastive representation learning has shown to be effective to learn representations from unlabeled data. However, much progress has been made in vision domains relying on data augmentations carefully designed using domain knowledge. In this work, we propose i-Mix, a simple yet effective domain-ag…