173 citations · 311 across the 10 of their papers we have counts for
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cs.LG2020★ 39 cited
A Survey of Deep Active Learning
Pengzhen Ren, Yun Xiao, Xiaojun Chang +5
Active learning (AL) attempts to maximize the performance gain of the model by marking the fewest samples. Deep learning (DL) is greedy for data and requires a large amount of data…
cs.CR2020★ 6 cited
Cloud-based Federated Boosting for Mobile Crowdsensing
Zhuzhu Wang, Yilong Yang, Yang Liu +3
The application of federated extreme gradient boosting to mobile crowdsensing apps brings several benefits, in particular high performance on efficiency and classification. However…