Variable Noise and Dimensionality Reduction for Sparse Gaussian processes.
Edward Lloyd SnelsonZoubin GhahramaniPublished in: UAI (2006)
Keyphrases
- gaussian processes
- dimensionality reduction
- covariance function
- relevance vector machine
- bayesian approaches
- gaussian process
- high dimensional
- gaussian process regression
- sparse representation
- low dimensional
- high dimensional data
- gaussian process models
- principal component analysis
- feature extraction
- human pose estimation
- multi task learning
- noise level
- missing data
- regression model
- multi task
- signal to noise ratio
- learning algorithm
- input data
- data points
- active learning
- training set
- training data
- feature selection