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stat.ML2020★ 3 cited
The effect of measurement error on clustering algorithms
Paulina Pankowska, Daniel L. Oberski
Clustering consists of a popular set of techniques used to separate data into interesting groups for further analysis. Many data sources on which clustering is performed are well-k…
stat.ML2020
Fair inference on error-prone outcomes
Laura Boeschoten, Erik-Jan van Kesteren, Ayoub Bagheri +1
Fair inference in supervised learning is an important and active area of research, yielding a range of useful methods to assess and account for fairness criteria when predicting gr…