Robust landmark graph-based clustering for high-dimensional data.
Ben YangJinghan WuAoran SunNaying GaoXuetao ZhangPublished in: Neurocomputing (2022)
Keyphrases
- high dimensional data
- low dimensional
- subspace clustering
- high dimensional
- high dimensionality
- nearest neighbor
- dimensionality reduction
- data points
- data sets
- data analysis
- high dimensions
- clustering high dimensional data
- high dimensional datasets
- high dimensional data sets
- lower dimensional
- similarity search
- input space
- dimensional data
- high dimensional spaces
- original data
- low rank
- manifold learning
- linear discriminant analysis
- subspace learning
- sparse representation
- dimension reduction
- input data
- k means
- small sample size
- nonlinear dimensionality reduction
- clustering algorithm
- variable weighting
- data clustering
- high dimensional feature spaces
- locally linear embedding
- multi dimensional
- feature space
- training data
- feature extraction
- machine learning