37 citations · 175 across the 13 of their papers we have counts for
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cs.LG2022★ 32 cited
Is Out-of-Distribution Detection Learnable?
Zhen Fang, Yixuan Li, Jie Lu +3
Supervised learning aims to train a classifier under the assumption that training and test data are from the same distribution. To ease the above assumption, researchers have studi…
cs.LG2022★ 17 cited
Multi-class Classification with Fuzzy-feature Observations: Theory and Algorithms
Guangzhi Ma, Jie Lu, Feng Liu +2
The theoretical analysis of multi-class classification has proved that the existing multi-class classification methods can train a classifier with high classification accuracy on t…
cs.LG2022★ 3 cited
Federated Class-Incremental Learning
Jiahua Dong, Lixu Wang, Zhen Fang +4
Federated learning (FL) has attracted growing attention via data-private collaborative training on decentralized clients. However, most existing methods unrealistically assume obje…