6 citations · 6 across the 3 of their papers we have counts for
3 papers
cs.LG2025
SHAP-Based Supervised Clustering for Sample Classification and the Generalized Waterfall Plot
Justin Lin, Julia Fukuyama
In this growing age of data and technology, large black-box models are becoming the norm due to their ability to handle vast amounts of data and learn incredibly complex input-outp…
stat.AP2025
DRtool: An Interactive Tool for Analyzing High-Dimensional Clusterings
Justin Lin, Julia Fukuyama
When faced with new data, we often conduct a cluster analysis to obtain a better understanding of the data's structure and the archetypical samples present in the data. However, th…
stat.AP2023★ 6 cited
Calibrating dimension reduction hyperparameters in the presence of noise
Justin Lin, Julia Fukuyama
The goal of dimension reduction tools is to construct a low-dimensional representation of high-dimensional data. These tools are employed for a variety of reasons such as noise red…