7 citations · 8 across the 4 of their papers we have counts for
4 papers
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…
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…
Hypothesis Testing for Class-Conditional Label Noise
Rafael Poyiadzi, Weisong Yang, Niall Twomey +1
In this paper we provide machine learning practitioners with tools to answer the question: is there class-conditional noise in my labels? In particular, we present hypothesis tests…
Detecting Signatures of Early-stage Dementia with Behavioural Models Derived from Sensor Data
Rafael Poyiadzi, Weisong Yang, Yoav Ben-Shlomo +5
There is a pressing need to automatically understand the state and progression of chronic neurological diseases such as dementia. The emergence of state-of-the-art sensing platform…