High-Dimensional Smoothed Entropy Estimation via Dimensionality Reduction.
Kristjan H. GreenewaldBrian KingsburyYuancheng YuPublished in: CoRR (2023)
Keyphrases
- dimensionality reduction
- high dimensional
- intrinsic dimensionality
- low dimensional
- high dimensional data
- high dimensionality
- estimation problems
- feature space
- principal component analysis
- manifold learning
- feature extraction
- linear discriminant analysis
- input space
- pattern recognition
- data points
- random projections
- dimension reduction
- nearest neighbor
- nonlinear dimensionality reduction
- dimensionality reduction methods
- high dimensional spaces
- estimation accuracy
- pattern recognition and machine learning
- estimation algorithm
- data representation
- principal components
- euclidean distance
- image processing
- mutual information
- information theory
- linear dimensionality reduction
- sparse representation
- similarity search
- parameter estimation
- high dimensional feature space
- multi dimensional
- feature selection
- metric space
- small sample size
- information entropy
- discriminant analysis
- metric learning