New Bounds for Hyperparameter Tuning of Regression Problems Across Instances.
Maria-Florina BalcanAnh NguyenDravyansh SharmaPublished in: NeurIPS (2023)
Keyphrases
- regression problems
- hyperparameters
- cross validation
- model selection
- linear regression
- genetic programming
- learning machines
- closed form
- random sampling
- parameter settings
- support vector
- gaussian processes
- upper bound
- sample size
- bayesian inference
- maximum likelihood
- gaussian process
- noise level
- bayesian framework
- lower bound
- high dimensional data
- support vector machine
- multi task
- incremental learning
- maximum a posteriori
- input space
- prior information
- em algorithm
- feature selection
- neural network
- missing values
- random forests
- worst case
- incomplete data
- logistic regression
- markov random field
- dimensionality reduction
- vc dimension