High-dimensional Bayesian optimization with sparse axis-aligned subspaces.
David ErikssonMartin JankowiakPublished in: UAI (2021)
Keyphrases
- high dimensional
- low dimensional
- sparse data
- high dimensional data
- dimensionality reduction
- lower dimensional
- data points
- manifold learning
- parameter space
- high dimensionality
- nearest neighbor
- optimization problems
- dimension reduction
- global optimization
- high dimension
- optimization process
- similarity search
- high dimensional spaces
- high dimensional feature spaces
- multi dimensional
- input space
- feature space
- variable selection
- data sets
- efficient optimization
- stochastic gradient
- convex optimization
- sparse coding
- microarray data
- sparse representation
- optimization algorithm
- additive models
- high dimensional data space
- bayesian learning
- metric space
- feature extraction