2 citations · 3 across the 2 of their papers we have counts for
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Bootstrapping the Operator Norm in High Dimensions: Error Estimation for Covariance Matrices and Sketching
Miles E. Lopes, N. Benjamin Erichson, Michael W. Mahoney
Although the operator (spectral) norm is one of the most widely used metrics for covariance estimation, comparatively little is known about the fluctuations of error in this norm.…
Estimating the Algorithmic Variance of Randomized Ensembles via the Bootstrap
Miles E. Lopes
Although the methods of bagging and random forests are some of the most widely used prediction methods, relatively little is known about their algorithmic convergence. In particula…
Bootstrapping Max Statistics in High Dimensions: Near-Parametric Rates Under Weak Variance Decay and Application to Functional and Multinomial Data
Miles E. Lopes, Zhenhua Lin, Hans-Georg Mueller
In recent years, bootstrap methods have drawn attention for their ability to approximate the laws of "max statistics" in high-dimensional problems. A leading example of such a stat…
A Residual Bootstrap for High-Dimensional Regression with Near Low-Rank Designs
Miles E. Lopes
We study the residual bootstrap (RB) method in the context of high-dimensional linear regression. Specifically, we analyze the distributional approximation of linear contrasts $c^{…