Inference of principal components of noisy correlation matrices with prior information.
Rémi MonassonPublished in: ACSSC (2016)
Keyphrases
- prior information
- principal components
- bayesian inference
- correlation matrix
- correlation coefficient
- principal component analysis
- prior knowledge
- dimensionality reduction
- hyperparameters
- multivariate data
- principal components analysis
- kernel space
- covariance matrix
- singular value decomposition
- bayesian model
- bayesian networks
- hyperplane
- feature set
- prior models
- prior distribution
- principal component regression
- spectral data
- incomplete data
- original data
- support vector machine
- high dimensional
- training set
- lower bound
- objective function