Sailing in high-dimensional spaces: Low-dimensional embeddings through angle preservation.
Jonas FischerRong MaPublished in: CoRR (2024)
Keyphrases
- low dimensional
- high dimensional
- manifold learning
- dimensionality reduction
- high dimensional data
- euclidean space
- principal component analysis
- dimension reduction
- vector space
- data points
- input space
- low dimensional spaces
- multidimensional scaling
- feature space
- lower dimensional
- linear subspace
- latent space
- nonlinear dimensionality reduction
- graph embedding
- rotation angle
- digital objects
- image processing
- manifold structure