Consistent Semi-Supervised Graph Regularization for High Dimensional Data.
Xiaoyi MaiRomain CouilletPublished in: CoRR (2020)
Keyphrases
- high dimensional data
- semi supervised
- dimensionality reduction
- subspace learning
- manifold learning
- graph construction
- semi supervised classification
- high dimensional
- low dimensional
- nearest neighbor
- low rank
- variable weighting
- graph laplacian
- data sets
- high dimensionality
- data points
- high dimensions
- subspace clustering
- underlying manifold
- labeled data
- labeled and unlabeled data
- data analysis
- semi supervised learning
- unlabeled data
- similarity search
- data distribution
- neighborhood graph
- input space
- random walk
- dimension reduction
- clustering high dimensional data
- kernel machines
- lower dimensional
- linear discriminant analysis
- input data
- small sample size
- pairwise
- dimensional data
- weighted graph
- high dimensional datasets
- active learning
- high dimensional spaces
- structured data
- supervised learning
- nonlinear dimensionality reduction
- high dimensional data sets
- query processing
- neural network