Dimensionality Reduction for Persistent Homology with Gaussian Kernels.
Jean-Daniel BoissonnatKunal DuttaPublished in: CoRR (2023)
Keyphrases
- gaussian kernels
- persistent homology
- dimensionality reduction
- high dimensional feature space
- kernel learning
- feature space
- topological features
- kernel function
- learning rate
- input space
- principal component analysis
- low dimensional
- computational geometry
- high dimensional
- feature extraction
- high dimensional data
- pattern recognition
- kernel principal component analysis
- multiple kernel learning
- reproducing kernel hilbert space
- feature selection
- principal components
- data points
- linear discriminant analysis
- gaussian kernel
- kernel methods
- euclidean distance
- kernel pca
- link prediction
- machine learning
- special case
- feature vectors
- image segmentation
- learning algorithm