1 citations · 2 across the 3 of their papers we have counts for
4 papers
Introducing a Family of Synthetic Datasets for Research on Bias in Machine Learning
William Blanzeisky, Pádraig Cunningham, Kenneth Kennedy
A significant impediment to progress in research on bias in machine learning (ML) is the availability of relevant datasets. This situation is unlikely to change much given the sens…
Exploring the Efficacy of Automatically Generated Counterfactuals for Sentiment Analysis
Linyi Yang, Jiazheng Li, Pádraig Cunningham +3
While state-of-the-art NLP models have been achieving the excellent performance of a wide range of tasks in recent years, important questions are being raised about their robustnes…
Using Pareto Simulated Annealing to Address Algorithmic Bias in Machine Learning
William Blanzeisky, Pádraig Cunningham
Algorithmic Bias can be due to bias in the training data or issues with the algorithm itself. These algorithmic issues typically relate to problems with model capacity and regulari…
Algorithmic Factors Influencing Bias in Machine Learning
William Blanzeisky, Pádraig Cunningham
It is fair to say that many of the prominent examples of bias in Machine Learning (ML) arise from bias that is there in the training data. In fact, some would argue that supervised…