Distributed High-dimensional Regression Under a Quantile Loss Function.
Xi ChenWeidong LiuXiaojun MaoZhuoyi YangPublished in: CoRR (2019)
Keyphrases
- loss function
- high dimensional
- reproducing kernel hilbert space
- gradient boosting
- support vector
- pairwise
- logistic regression
- empirical risk
- risk minimization
- learning to rank
- stochastic gradient descent
- boosting framework
- similarity search
- regularization term
- square loss
- support vector regression
- high dimensional data
- model selection
- regression problems
- boosting algorithms
- variable selection
- base learners
- regression model
- hinge loss
- nearest neighbor
- information retrieval