High-Dimensional Bayesian Optimization with Sparse Axis-Aligned Subspaces.
David ErikssonMartin JankowiakPublished in: CoRR (2021)
Keyphrases
- high dimensional
- low dimensional
- sparse data
- high dimensional data
- similarity search
- data points
- lower dimensional
- dimensionality reduction
- feature space
- multi dimensional
- optimization algorithm
- manifold learning
- high dimensionality
- parameter space
- high dimensional feature spaces
- nearest neighbor
- dimension reduction
- high dimension
- optimization problems
- bayesian networks
- global optimization
- input space
- sparse bayesian learning
- low dimensional spaces
- optimization process
- metric space
- high dimensional data space
- microarray data
- sparse pca
- subspace learning
- objective function