Federated singular value decomposition for high dimensional data.
Anne HartebrodtRichard RöttgerDavid B. BlumenthalPublished in: CoRR (2022)
Keyphrases
- high dimensional data
- singular value decomposition
- dimensionality reduction
- high dimensional
- low dimensional
- dimension reduction
- singular values
- nearest neighbor
- low rank
- high dimensionality
- principal component analysis
- data points
- input space
- subspace clustering
- data sets
- latent semantic indexing
- data analysis
- original data
- lower dimensional
- similarity search
- manifold learning
- pattern recognition
- missing values
- least squares
- random projections
- linear discriminant analysis
- sparse representation
- subspace learning
- euclidean distance
- feature extraction
- data matrix
- null space
- principal components
- feature space
- text data
- gene expression data
- feature selection
- machine learning