Preserving local densities in low-dimensional embeddings.
Jonas FischerRebekka BurkholzJilles VreekenPublished in: CoRR (2023)
Keyphrases
- low dimensional
- high dimensional
- probability density function
- dimensionality reduction
- manifold learning
- high dimensional data
- euclidean space
- data points
- vector space
- principal component analysis
- dimension reduction
- input space
- lower dimensional
- feature space
- neural network
- linear subspace
- nonlinear dimensionality reduction
- probability density
- subspace learning
- latent space
- low dimensional spaces
- similarity search
- computer vision
- binary codes
- feature vectors
- locally linear embedding
- machine learning