Vector ℓ0 latent-space principal component analysis.
Martin LuessiMatti S. HämäläinenVictor SoloPublished in: ICASSP (2014)
Keyphrases
- latent space
- principal component analysis
- low dimensional
- lower dimensional
- dimensionality reduction
- vector space
- feature space
- latent variables
- dimension reduction
- high dimensional
- feature extraction
- manifold learning
- linear discriminant analysis
- face recognition
- random projections
- gaussian process
- higher dimensional
- high dimensional data
- covariance matrix
- parameter space
- high dimensional spaces
- feature vectors
- gaussian processes
- gaussian process latent variable models
- probabilistic latent semantic analysis
- singular value decomposition
- generative model
- computer vision
- gaussian mixture
- matrix factorization
- pattern recognition
- image processing
- negative matrix factorization
- distance metric