7 citations · 8 across the 4 of their papers we have counts for
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cs.LG2023★ 1 cited
Hypothesis Testing for Class-Conditional Noise Using Local Maximum Likelihood
Weisong Yang, Rafael Poyiadzi, Niall Twomey +1
In supervised learning, automatically assessing the quality of the labels before any learning takes place remains an open research question. In certain particular cases, hypothesis…
cs.LG2023
When the Ground Truth is not True: Modelling Human Biases in Temporal Annotations
Taku Yamagata, Emma L. Tonkin, Benjamin Arana Sanchez +5
In supervised learning, low quality annotations lead to poorly performing classification and detection models, while also rendering evaluation unreliable. This is particularly appa…