High Dimensional Bayesian Optimization Assisted by Principal Component Analysis.
Elena RaponiHao WangMariusz BujnySimonetta BoriaCarola DoerrPublished in: PPSN (1) (2020)
Keyphrases
- principal component analysis
- high dimensional
- dimensionality reduction
- low dimensional
- dimension reduction
- feature space
- principal components
- similarity search
- optimization algorithm
- data points
- lower dimensional
- face images
- optimization method
- high dimensionality
- independent component analysis
- global optimization
- efficient optimization
- covariance matrix
- high dimensional data
- bayesian networks
- manifold learning
- sparse data
- bayesian estimation
- high dimensional problems
- face recognition
- discriminant analysis
- singular value decomposition
- multi dimensional
- feature extraction
- linear discriminant analysis
- posterior probability
- bayesian inference
- combinatorial optimization
- data driven
- bayesian learning
- computer vision