11 citations · 13 across the 2 of their papers we have counts for
2 papers
stat.ML2019★ 11 cited
Sufficient Representations for Categorical Variables
Jonathan Johannemann, Vitor Hadad, Susan Athey +1
Many learning algorithms require categorical data to be transformed into real vectors before it can be used as input. Often, categorical variables are encoded as one-hot (or dummy)…
stat.ML2019★ 2 cited
Spectral Overlap and a Comparison of Parameter-Free, Dimensionality Reduction Quality Metrics
Jonathan Johannemann, Robert Tibshirani
Nonlinear dimensionality reduction methods are a popular tool for data scientists and researchers to visualize complex, high dimensional data. However, while these methods continue…