283 citations · 546 across the 36 of their papers we have counts for
4 papers · 1 filter
A Model or 603 Exemplars: Towards Memory-Efficient Class-Incremental Learning
Da-Wei Zhou, Qi-Wei Wang, Han-Jia Ye +1
Real-world applications require the classification model to adapt to new classes without forgetting old ones. Correspondingly, Class-Incremental Learning (CIL) aims to train a mode…
FOSTER: Feature Boosting and Compression for Class-Incremental Learning
Fu-Yun Wang, Da-Wei Zhou, Han-Jia Ye +1
The ability to learn new concepts continually is necessary in this ever-changing world. However, deep neural networks suffer from catastrophic forgetting when learning new categori…
Forward Compatible Few-Shot Class-Incremental Learning
Da-Wei Zhou, Fu-Yun Wang, Han-Jia Ye +3
Novel classes frequently arise in our dynamically changing world, e.g., new users in the authentication system, and a machine learning model should recognize new classes without fo…
Few-Shot Class-Incremental Learning by Sampling Multi-Phase Tasks
Da-Wei Zhou, Han-Jia Ye, Liang Ma +3
New classes arise frequently in our ever-changing world, e.g., emerging topics in social media and new types of products in e-commerce. A model should recognize new classes and mea…