Subspace Clustering of Very Sparse High-Dimensional Data.
Hankui PengNicos G. PavlidisIdris A. EckleyIoannis TsalamanisPublished in: CoRR (2019)
Keyphrases
- subspace clustering
- high dimensional data
- high dimensional
- sparse representation
- low dimensional
- dimensionality reduction
- subspace clusters
- clustering high dimensional data
- nearest neighbor
- high dimensionality
- data sets
- data analysis
- high dimensional feature spaces
- original data
- data points
- dimension reduction
- random projections
- similarity search
- low rank
- manifold learning
- high dimensional datasets
- complex data
- subspace learning
- linear discriminant analysis
- dimensional data
- sparse coding
- input space
- underlying manifold
- subspace projections
- subspace clustering algorithms
- lower dimensional
- input data
- multi dimensional
- clustering method
- high dimensional spaces
- feature vectors
- data structure
- clustering algorithm
- image processing
- computer vision
- neural network