166 citations · 595 across the 71 of their papers we have counts for
Showing 2020 · math.STShow all
2 papers · 2 filters
math.ST2020
Selecting the number of components in PCA via random signflips
David Hong, Yue Sheng, Edgar Dobriban
Principal component analysis (PCA) is a foundational tool in modern data analysis, and a crucial step in PCA is selecting the number of components to keep. However, classical selec…
math.ST2020★ 8 cited
How to reduce dimension with PCA and random projections?
Fan Yang, Sifan Liu, Edgar Dobriban +1
In our "big data" age, the size and complexity of data is steadily increasing. Methods for dimension reduction are ever more popular and useful. Two distinct types of dimension red…