High Dimensional Bayesian Optimization via Supervised Dimension Reduction.
Miao ZhangHuiqi LiSteven W. SuPublished in: CoRR (2019)
Keyphrases
- dimension reduction
- high dimensional
- low dimensional
- high dimensional problems
- high dimensionality
- high dimensional data
- variable selection
- unsupervised learning
- feature selection
- dimensionality reduction
- principal component analysis
- feature extraction
- data mining and machine learning
- feature space
- manifold learning
- linear discriminant analysis
- supervised learning
- singular value decomposition
- random projections
- data points
- partial least squares
- high dimensional data analysis
- dimension reduction methods
- small sample size
- lower dimensional
- similarity search
- cluster analysis
- nearest neighbor
- semi supervised
- pattern recognition
- discriminative information
- sparse coding
- discriminant analysis
- neural network
- input data
- input image
- machine learning