Interpolating between Clustering and Dimensionality Reduction with Gromov-Wasserstein.
Hugues Van AsselCédric Vincent-CuazTitouan VayerRémi FlamaryNicolas CourtyPublished in: CoRR (2023)
Keyphrases
- dimensionality reduction
- high dimensional data
- high dimensionality
- pattern recognition and machine learning
- data points
- clustering algorithm
- clustering method
- high dimensional
- principal components analysis
- unsupervised learning
- categorical data
- feature extraction
- k means
- cluster analysis
- hierarchical clustering
- principal components
- structure preserving
- graph theoretic
- multidimensional scaling
- manifold learning
- fuzzy clustering
- dealing with high dimensional data
- self organizing maps
- low dimensional
- pattern recognition
- linear discriminant analysis
- subspace clustering
- principal component analysis
- feature space
- dimensionality reduction methods
- unsupervised feature selection
- face recognition
- linear dimensionality reduction
- image processing
- feature selection