Data-efficient and Computation-efficient Deep Learning
We are interested in developing computation-efficent deep learning algorithms and data-efficient deep learning methods including high-quality data synthesis methods, efficient image annotation systems, label-efficient learning strategies (e.g. self-supervised learning, weakly supervised learning, domain adaptation, and semi-supervised learning, etc).