Parallel Gaussian Process Regression with Low-Rank Covariance Matrix Approximations.
Jie ChenNannan CaoKian Hsiang LowRuofei OuyangColin Keng-Yan TanPatrick JailletPublished in: UAI (2013)
Keyphrases
- covariance matrix
- low rank
- gaussian process regression
- eigendecomposition
- linear combination
- convex optimization
- covariance matrices
- missing data
- matrix factorization
- singular value decomposition
- gaussian process
- gaussian processes
- principal component analysis
- high dimensional data
- sample size
- semi supervised
- kernel matrix
- high order
- collaborative filtering
- similarity measure
- objective function
- machine learning
- closed form
- model selection