3 papers
cs.LG2025
Learning to Learn from APIs: Black-Box Data-Free Meta-Learning
Zixuan Hu, Li Shen, Zhenyi Wang +3
Data-free meta-learning (DFML) aims to enable efficient learning of new tasks by meta-learning from a collection of pre-trained models without access to the training data. Existing…
cs.LG2025
Architecture, Dataset and Model-Scale Agnostic Data-free Meta-Learning
Zixuan Hu, Li Shen, Zhenyi Wang +3
The goal of data-free meta-learning is to learn useful prior knowledge from a collection of pre-trained models without accessing their training data. However, existing works only s…
cs.LG2024
A Comprehensive Survey of Forgetting in Deep Learning Beyond Continual Learning
Zhenyi Wang, Enneng Yang, Li Shen +1
Forgetting refers to the loss or deterioration of previously acquired knowledge. While existing surveys on forgetting have primarily focused on continual learning, forgetting is a…