36 citations · 41 across the 3 of their papers we have counts for
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math.ST2020
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…
math.ST2019
Ridge Regression: Structure, Cross-Validation, and Sketching
Sifan Liu, Edgar Dobriban
We study the following three fundamental problems about ridge regression: (1) what is the structure of the estimator? (2) how to correctly use cross-validation to choose the regula…
math.ST2019
WONDER: Weighted one-shot distributed ridge regression in high dimensions
Edgar Dobriban, Yue Sheng
In many areas, practitioners need to analyze large datasets that challenge conventional single-machine computing. To scale up data analysis, distributed and parallel computing appr…