81 citations · 111 across the 7 of their papers we have counts for
Showing 2021Show all
3 papers · 1 filter
cs.LG2021
Omni-Training: Bridging Pre-Training and Meta-Training for Few-Shot Learning
Yang Shu, Zhangjie Cao, Jinghan Gao +3
Few-shot learning aims to fast adapt a deep model from a few examples. While pre-training and meta-training can create deep models powerful for few-shot generalization, we find tha…
cs.LG2021★ 3 cited
Zoo-Tuning: Adaptive Transfer from a Zoo of Models
Yang Shu, Zhi Kou, Zhangjie Cao +2
With the development of deep networks on various large-scale datasets, a large zoo of pretrained models are available. When transferring from a model zoo, applying classic single-m…
cs.CV2021★ 8 cited
Open Domain Generalization with Domain-Augmented Meta-Learning
Yang Shu, Zhangjie Cao, Chenyu Wang +2
Leveraging datasets available to learn a model with high generalization ability to unseen domains is important for computer vision, especially when the unseen domain's annotated da…