1 citations · 2 across the 4 of their papers we have counts for
4 papers
Adaptive Margin Global Classifier for Exemplar-Free Class-Incremental Learning
Zhongren Yao, Xiaobin Chang
Exemplar-free class-incremental learning (EFCIL) presents a significant challenge as the old class samples are absent for new task learning. Due to the severe imbalance between old…
Consistent Prompting for Rehearsal-Free Continual Learning
Zhanxin Gao, Jun Cen, Xiaobin Chang
Continual learning empowers models to adapt autonomously to the ever-changing environment or data streams without forgetting old knowledge. Prompt-based approaches are built on fro…
Generalizable Two-Branch Framework for Image Class-Incremental Learning
Chao Wu, Xiaobin Chang, Ruixuan Wang
Deep neural networks often severely forget previously learned knowledge when learning new knowledge. Various continual learning (CL) methods have been proposed to handle such a cat…
Dynamic Residual Classifier for Class Incremental Learning
Xiuwei Chen, Xiaobin Chang
The rehearsal strategy is widely used to alleviate the catastrophic forgetting problem in class incremental learning (CIL) by preserving limited exemplars from previous tasks. With…