On Effects of Condition Number of Regression Matrix upon Hyper-parameter Estimators for Kernel-based Regularization Methods.
Yue JuTianshi ChenBi-Qiang MuLennart LjungPublished in: CoRR (2020)
Keyphrases
- condition number
- regression model
- hyperparameters
- model selection
- linear algebra
- support vector
- interior point methods
- cross validation
- parameter settings
- closed form
- random sampling
- kernel methods
- noise level
- bayesian inference
- support vector machine
- total variation
- sample size
- machine learning
- maximum a posteriori
- bayesian framework
- semi parametric