An empirical study of the sample size variability of optimal active learning using Gaussian process regression.
Flora Yu-Hui YehMarcus GallagherPublished in: IJCNN (2008)
Keyphrases
- sample size
- gaussian process regression
- active learning
- random sampling
- gaussian process
- experimental design
- hyperparameters
- worst case
- model selection
- gaussian processes
- small sample
- progressive sampling
- generalization error
- upper bound
- semi supervised
- covariance matrix
- machine learning
- optimal solution
- statistical power
- data sets
- transfer learning
- training set
- objective function
- sample complexity
- decision trees
- learning algorithm
- random sample
- statistical hypothesis testing