Feature-Robust Optimal Transport for High-Dimensional Data.
Mathis PetrovichChao LiangRyoma SatoYanbin LiuYao-Hung Hubert TsaiLinchao ZhuYi YangRuslan SalakhutdinovMakoto YamadaPublished in: ECML/PKDD (5) (2022)
Keyphrases
- high dimensional data
- dimensionality reduction
- low dimensional
- high dimensionality
- nearest neighbor
- high dimensional
- data sets
- high dimensions
- dimension reduction
- subspace clustering
- input space
- data points
- clustering high dimensional data
- similarity search
- data distribution
- high dimensional spaces
- missing values
- data analysis
- manifold learning
- dimensional data
- high dimensional datasets
- low rank
- original data
- linear discriminant analysis
- lower dimensional
- nonlinear dimensionality reduction
- sparse representation
- small sample size
- variable selection
- input data
- high dimensional data sets
- feature set
- variable weighting
- subspace learning
- text data
- feature subset
- database
- data mining
- machine learning
- principal component analysis
- feature space