Variable noise and dimensionality reduction for sparse Gaussian processes.
Edward Lloyd SnelsonZoubin GhahramaniPublished in: CoRR (2012)
Keyphrases
- gaussian processes
- dimensionality reduction
- covariance function
- relevance vector machine
- bayesian approaches
- gaussian process
- high dimensional
- gaussian process regression
- noise level
- sparse representation
- hyperparameters
- missing data
- multi task learning
- principal component analysis
- human pose estimation
- noise reduction
- signal to noise ratio
- gaussian process models
- feature extraction
- low dimensional
- data sets
- noisy images
- kernel pca
- bayesian framework
- support vector machine
- data points