Intrinsic Topological Transforms via the Distance Kernel Embedding.
Clément MariaSteve OudotElchanan SolomonPublished in: SoCG (2020)
Keyphrases
- component analysis
- laplacian eigenmaps
- kernel function
- intrinsic dimension
- euclidean distance
- distance metric
- distance transform
- geodesic distance
- graph embedding
- kernel regression
- kernel methods
- manifold learning
- convolution kernel
- data sets
- topological features
- positive definite
- watermarking technique
- multiple kernel learning
- distance function
- distance measure
- pairwise
- support vector