High-Dimensional Multivariate Forecasting with Low-Rank Gaussian Copula Processes.
David SalinasMichael Bohlke-SchneiderLaurent CallotRoberto MedicoJan GasthausPublished in: CoRR (2019)
Keyphrases
- low rank
- high dimensional
- high dimensional data
- linear combination
- dependence structure
- low rank matrix
- convex optimization
- missing data
- singular value decomposition
- matrix completion
- matrix factorization
- gaussian mixture
- marginal distributions
- high order
- low dimensional
- rank minimization
- matrix decomposition
- dimensionality reduction
- minimization problems
- kernel matrix
- singular values
- trace norm
- semi supervised
- data points
- robust principal component analysis
- input space
- data mining
- sparse coding
- feature selection
- manifold learning
- missing values
- non rigid structure from motion
- machine learning
- regression model
- nearest neighbor
- low rank matrices
- neural network