High-dimensional Bayesian Optimization via Covariance Matrix Adaptation Strategy.
Lam NgoHuong HaJeffrey ChanVu NguyenHongyu ZhangPublished in: CoRR (2024)
Keyphrases
- covariance matrix
- high dimensional
- class conditional densities
- covariance matrices
- cma es
- sample size
- principal component analysis
- mahalanobis distance
- global optimization
- bayesian networks
- dimensionality reduction
- optimization algorithm
- positive definite
- low dimensional
- evolution strategy
- maximum likelihood
- gaussian mixture
- pseudo inverse
- parameter space
- optimization problems
- similarity search
- estimation error
- eigendecomposition
- geometrical interpretation
- optimization process
- data points
- differential evolution
- feature space
- correlation matrix
- high dimensional data
- multivariate gaussian
- search algorithm
- objective function
- optimization method
- eigenvalues and eigenvectors
- principal components