Multilinear Kernel Regression and Imputation via Manifold Learning.
Duc Thien NguyenKonstantinos SlavakisPublished in: CoRR (2024)
Keyphrases
- kernel regression
- manifold learning
- subspace learning
- dimensionality reduction
- missing values
- missing data
- regression model
- high dimensional data
- low dimensional
- nadaraya watson
- higher order
- principal component analysis
- semi supervised
- regression methods
- high dimensional
- feature extraction
- parameter optimization
- dimension reduction
- neural network
- high dimensionality
- support vector
- sparse representation
- data points
- pattern recognition
- singular value decomposition
- euclidean distance
- matrix factorization
- incomplete data
- genetic algorithm ga
- feature space
- clustering algorithm