Mar 31, 2021 · Abstract:Deep neural networks (DNNs) have the capacity to fit extremely noisy labels nonetheless they tend to learn data with clean labels ...
As can be seen, two models utilize their low entropy predictions determined by a given threshold to correct labels for each other. We empirically demonstrate ...
It also shows the advantage in maintaining more training samples than previous methods. Then, we power this entropy criterion with the Collaborative Label ...
It also shows the advantage in maintaining more training samples than previous methods. Then, we power this entropy criterion with the Collaborative Label ...
Mar 31, 2021 · Collaborative Label Correction via Entropy Thresholding ... Deep neural networks (DNNs) have the capacity to fit extremely noisy labels ...
张娅,zhangya,上海交大研究生院主页平台管理系统, Collaborative label correction via entropy thresholding张娅,Ya Zhang.
It also shows the advantage in maintaining more training samples than previous methods. Then, we power this entropy criterion with the Collaborative Label ...
Active label correction using robust parameter update and entropy propagation. [Paper]; A data-centric approach for improving ambiguous labels with combined ...
Collaborative Label Correction via Entropy Thresholding. ICDM 2019: 1390-1395; 2018. [j3]. view. electronic edition via DOI; unpaywalled version; references ...
Collaborative Label Correction via Entropy Thresholding Hao Wu, Jiangchao Yao, Jiajie Wang, Yinru Chen, Ya Zhang, Yanfeng Wang. International Conference on ...
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