Robust and compact maximum margin clustering for high-dimensional data.
Hakan CevikalpEdward ChomePublished in: Neural Comput. Appl. (2024)
Keyphrases
- high dimensional data
- dimensionality reduction
- nearest neighbor
- high dimensional
- low dimensional
- high dimensions
- subspace clustering
- high dimensionality
- similarity search
- data points
- data sets
- dimension reduction
- input space
- original data
- sparse representation
- data analysis
- clustering high dimensional data
- high dimensional spaces
- linear discriminant analysis
- complex data
- dimensional data
- subspace learning
- lower dimensional
- high dimensional data sets
- manifold learning
- data distribution
- low rank
- high dimensional datasets
- nonlinear dimensionality reduction
- feature extraction
- binary codes
- text data
- knn
- data streams
- low dimensional structure