Positive Semi-definite Embedding for Dimensionality Reduction and Out-of-Sample Extensions.
Michaël FanuelAntoine AspeelJean-Charles DelvenneJohan A. K. SuykensPublished in: SIAM J. Math. Data Sci. (2022)
Keyphrases
- dimensionality reduction
- positive semi definite
- metric learning
- nonlinear dimensionality reduction
- graph embedding
- graph kernels
- low dimensional
- data representation
- principal component analysis
- kernel function
- kernel methods
- high dimensional data
- dot product
- manifold learning
- feature space
- feature extraction
- similarity function
- high dimensional
- vector space
- kernel pca
- feature selection
- input space
- linear discriminant analysis
- pattern recognition
- principal components
- kernel matrix
- singular value decomposition
- distance metric
- machine learning
- random projections
- face recognition
- reproducing kernel hilbert space
- label information
- perceptron algorithm
- semi supervised