Federated singular value decomposition for high-dimensional data.
Anne HartebrodtRichard RöttgerDavid B. BlumenthalPublished in: Data Min. Knowl. Discov. (2024)
Keyphrases
- singular value decomposition
- high dimensional data
- dimensionality reduction
- low dimensional
- high dimensional
- principal component analysis
- dimension reduction
- high dimensionality
- nearest neighbor
- subspace clustering
- low rank
- singular values
- data analysis
- similarity search
- latent semantic indexing
- manifold learning
- least squares
- feature space
- data sets
- input space
- data points
- linear discriminant analysis
- original data
- lower dimensional
- sparse representation
- subspace learning
- random projections
- pattern recognition
- missing values
- principal components
- feature extraction
- feature selection
- input data
- data mining
- gene expression data
- information retrieval
- computer vision
- kernel function