Dimensionality reduction on complex vector spaces for dynamic weighted Euclidean distance.
Paolo PellizzoniFrancesco SilvestriPublished in: CoRR (2022)
Keyphrases
- machine learning
- euclidean distance
- dimensionality reduction
- vector space
- intrinsic dimensionality
- distance measure
- euclidean space
- pattern recognition
- low dimensional
- feature selection
- cosine similarity
- feature vectors
- cosine distance
- distance metric
- data points
- high dimensional spaces
- similarity measurement
- distance function
- principal component analysis
- feature space
- riemannian manifolds
- high dimensional
- similarity search
- high dimensional data
- high dimensionality
- data representation
- similarity measure
- feature extraction
- random projections
- graph classification
- dimensionality reduction methods
- manhattan distance
- metric space
- input space
- graph matching
- shape analysis
- nearest neighbor
- geodesic distance
- dynamic time warping
- nonlinear dimensionality reduction
- computer vision
- manifold learning
- square root