Subspace Embedding and Linear Regression with Orlicz Norm.
Alexandr AndoniChengyu LinYing ShengPeilin ZhongRuiqi ZhongPublished in: CoRR (2018)
Keyphrases
- linear regression
- least squares
- hilbert space
- locality preserving projections
- regression methods
- regression problems
- nonlinear regression
- low dimensional
- ridge regression
- principal component analysis
- dimensionality reduction
- subspace learning
- linear models
- objective function
- linear regression model
- high dimensional
- locally weighted
- feature space
- multivariate regression
- kernel regression
- regression trees
- high dimensional data
- regression method
- subspace methods
- generalized linear models
- linear predictors