Sharp Bias-variance Tradeoffs of Hard Parameter Sharing in High-dimensional Linear Regression.
Hongyang R. ZhangFan YangSen WuWeijie J. SuChristopher RéPublished in: CoRR (2020)
Keyphrases
- linear regression
- bias variance
- high dimensional
- generalized linear models
- trade off
- least squares
- parameter space
- regression problems
- low dimensional
- regression methods
- nonlinear regression
- ridge regression
- linear regression model
- bias variance decomposition
- nearest neighbor
- locally weighted
- low variance
- linear models
- multivariate regression
- regression trees
- regression method
- variable selection
- high dimensional data
- predictor variables
- machine learning
- bias variance analysis
- input space
- dimension reduction
- cross validation
- kernel function
- data points
- feature extraction