Kernels and learning curves for Gaussian process regression on random graphs.
Peter SollichMatthew UrryCamille CotiPublished in: NIPS (2009)
Keyphrases
- learning curves
- gaussian process regression
- gaussian processes
- random graphs
- gaussian process
- graph theoretic
- phase transition
- feature space
- multi task
- kernel methods
- small world
- kernel function
- bayesian framework
- undirected graph
- hyperparameters
- learning curve
- machine learning
- regression model
- machine learning algorithms
- support vector