Parallel Gaussian Process Regression with Low-Rank Covariance Matrix Approximations.
Jie ChenNannan CaoKian Hsiang LowRuofei OuyangColin Keng-Yan TanPatrick JailletPublished in: CoRR (2014)
Keyphrases
- covariance matrix
- low rank
- gaussian process regression
- eigendecomposition
- matrix factorization
- singular value decomposition
- principal component analysis
- covariance matrices
- gaussian process
- missing data
- linear combination
- convex optimization
- semi supervised
- high order
- gaussian processes
- high dimensional data
- sample size
- kernel matrix
- collaborative filtering
- higher order
- active learning
- data sets
- regression model
- dimensionality reduction
- least squares
- multi class