Corrupted and missing predictors: Minimax bounds for high-dimensional linear regression.
Po-Ling LohMartin J. WainwrightPublished in: ISIT (2012)
Keyphrases
- linear regression
- high dimensional
- generalized linear models
- predictor variables
- loss bounds
- worst case
- linear predictors
- least squares
- upper bound
- regression problems
- missing data
- regression methods
- ridge regression
- linear regression model
- regret bounds
- low dimensional
- lower bound
- locally weighted
- nonlinear regression
- feature space
- square loss
- missing values
- regression trees
- variable selection
- dimensionality reduction
- data points
- high dimensional data
- regression method
- classification trees
- evaluation function
- nearest neighbor
- input space
- kernel function