Distributed High-dimensional Regression Under a Quantile Loss Function.
Xi ChenWeidong LiuXiaojun MaoZhuoyi YangPublished in: J. Mach. Learn. Res. (2020)
Keyphrases
- loss function
- high dimensional
- gradient boosting
- reproducing kernel hilbert space
- support vector
- pairwise
- logistic regression
- learning to rank
- low dimensional
- convex loss functions
- boosting framework
- empirical risk
- regression model
- risk minimization
- input space
- variable selection
- square loss
- gaussian kernels
- feature space
- model selection
- data points
- stochastic gradient descent
- regularization term
- random forests
- hinge loss
- solution path
- support vector regression
- linear regression
- dimensionality reduction