Measuring the Algorithmic Convergence of Randomized Ensembles: The Regression Setting.
Miles E. LopesSuofei WuThomas C. M. LeePublished in: CoRR (2019)
Keyphrases
- upper confidence bound
- regression model
- convergence rate
- model selection
- decision trees
- regression trees
- polynomial regression
- support vector regression
- linear regression
- initial conditions
- simple linear
- regression methods
- ensemble methods
- ensemble learning
- gaussian processes
- regression analysis
- reproducing kernel hilbert space
- iterative algorithms
- global convergence
- ridge regression
- randomized algorithm
- feature space
- contextual bandit
- support vector