Robust high-dimensional low-rank matrix estimation: optimal rate and data-adaptive tuning
The matrix lasso, which minimizes a least-squared loss function with the nuclear-norm
regularization, offers a generally applicable paradigm for high-dimensional low-rank matrix …
regularization, offers a generally applicable paradigm for high-dimensional low-rank matrix …
Investigations in Ultra High-Dimensional Models
M Law - 2022 - deepblue.lib.umich.edu
This dissertation considers the problem of estimation and inference in four high-dimensional
models:(i) high-dimensional linear models,(ii) high-dimensional linear mixed effects …
models:(i) high-dimensional linear models,(ii) high-dimensional linear mixed effects …