46 citations · 112 across the 10 of their papers we have counts for
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cs.CV2022★ 1 cited
Incremental Learning Meets Transfer Learning: Application to Multi-site Prostate MRI Segmentation
Chenyu You, Jinlin Xiang, Kun Su +5
Many medical datasets have recently been created for medical image segmentation tasks, and it is natural to question whether we can use them to sequentially train a single model th…
cs.LG2022★ 6 cited
A Cross-City Federated Transfer Learning Framework: A Case Study on Urban Region Profiling
Gaode Chen, Yijun Su, Xinghua Zhang +6
Data insufficiency problems (i.e., data missing and label scarcity) caused by inadequate services and infrastructures or imbalanced development levels of cities have seriously affe…
cs.LG2022★ 4 cited
TKIL: Tangent Kernel Approach for Class Balanced Incremental Learning
Jinlin Xiang, Eli Shlizerman
When learning new tasks in a sequential manner, deep neural networks tend to forget tasks that they previously learned, a phenomenon called catastrophic forgetting. Class increment…