83 citations · 224 across the 27 of their papers we have counts for
Showing 2021 · stat.MLShow all
2 papers · 2 filters
stat.ML2021★ 2 cited
Supervised Linear Dimension-Reduction Methods: Review, Extensions, and Comparisons
Shaojie Xu, Joel Vaughan, Jie Chen +2
Principal component analysis (PCA) is a well-known linear dimension-reduction method that has been widely used in data analysis and modeling. It is an unsupervised learning techniq…
stat.ML2021★ 10 cited
Bias, Fairness, and Accountability with AI and ML Algorithms
Nengfeng Zhou, Zach Zhang, Vijayan N. Nair +3
The advent of AI and ML algorithms has led to opportunities as well as challenges. In this paper, we provide an overview of bias and fairness issues that arise with the use of ML a…