Re-Examining Linear Embeddings for High-Dimensional Bayesian Optimization.
Benjamin LethamRoberto CalandraAkshara RaiEytan BakshyPublished in: CoRR (2020)
Keyphrases
- high dimensional
- low dimensional
- dimensionality reduction
- optimization algorithm
- high dimensional data
- low dimensional spaces
- multi dimensional
- optimization problems
- efficient optimization
- manifold learning
- sparse data
- variable selection
- optimization method
- highly non linear
- bayesian learning
- constrained optimization
- bayesian inference
- neural network
- similarity search
- maximum likelihood
- feature space
- linear systems
- input space