High-dimensional Experimental Design and Kernel Bandits.
Romain CamilleriKevin JamiesonJulian Katz-SamuelsPublished in: ICML (2021)
Keyphrases
- experimental design
- high dimensional
- kernel function
- feature space
- active learning
- kernel methods
- empirical studies
- experimental designs
- feature selection
- dimensionality reduction
- nearest neighbor
- low dimensional
- high dimensionality
- data points
- sample size
- high dimensional data
- virtual learning environments
- machine learning
- learning strategies
- class imbalance
- support vector
- training samples
- learning process