High-Dimensional Bayesian Optimization with Manifold Gaussian Processes.
Riccardo MoriconiK. S. Sesh KumarMarc Peter DeisenrothPublished in: CoRR (2019)
Keyphrases
- gaussian processes
- high dimensional
- low dimensional
- gaussian process
- bayesian approaches
- gaussian process regression
- multi task learning
- relevance vector machine
- latent space
- hyperparameters
- manifold learning
- gaussian process models
- covariance function
- bayesian methods
- parameter space
- multi task
- feature space
- high dimensional data
- model selection
- human pose estimation
- dimensionality reduction
- training data
- pairwise
- graphical models
- principal component analysis
- data points