Block-diagonal precision matrix regularization for ultra-high dimensional data.
Yihe YangHongsheng DaiJianxin PanPublished in: Comput. Stat. Data Anal. (2023)
Keyphrases
- high dimensional data
- block diagonal
- affinity matrix
- low rank
- subspace clustering
- kernel matrix
- dimensionality reduction
- semidefinite programming
- high dimensional
- nearest neighbor
- input space
- augmented lagrangian
- low dimensional
- data sets
- high dimensionality
- data analysis
- linear programming problems
- reproducing kernel hilbert space
- dimension reduction
- manifold learning
- similarity search
- data points
- variable selection
- regularization parameter
- sparse representation
- locally linear embedding
- training samples
- pattern recognition
- spectral clustering
- interior point methods
- manifold structure
- input data