Insightful Dimensionality Reduction with Very Low Rank Variable Subsets.
Bruno OrdozgoitiSachith PaiMarta KolczynskaPublished in: WWW (2021)
Keyphrases
- low rank
- dimensionality reduction
- high dimensional data
- singular value decomposition
- low rank matrix
- missing data
- matrix completion
- low dimensional
- high dimensional
- linear combination
- high dimensionality
- matrix factorization
- feature extraction
- matrix decomposition
- convex optimization
- rank minimization
- principal component analysis
- kernel matrix
- semi supervised
- high order
- manifold learning
- pattern recognition
- trace norm
- feature selection
- data analysis
- data points
- sparse representation
- singular values
- robust principal component analysis
- original data
- data matrix
- kernel learning
- data representation
- euclidean distance
- random projections
- minimization problems
- feature space
- data mining
- non rigid structure from motion
- low rank matrices
- missing values
- denoising
- subspace learning
- metric learning
- object detection
- higher order