Reproducing kernel Hilbert spaces on manifolds: Sobolev and Diffusion spaces.
Ernesto De VitoNicole MückeLorenzo RosascoPublished in: CoRR (2019)
Keyphrases
- reproducing kernel hilbert space
- hilbert space
- riemannian manifolds
- reproducing kernel
- euclidean space
- finite dimensional
- infinite dimensional
- loss function
- kernel methods
- von neumann
- kernel function
- anisotropic diffusion
- gaussian kernels
- diffusion process
- density estimation
- uniform convergence
- distance measure
- special case
- learning theory
- higher dimensional
- data dependent
- input space
- scale spaces
- domain adaptation
- shape analysis
- multivariate time series
- low dimensional
- vector space
- real valued
- euclidean distance
- data points
- convex sets
- linear model
- gaussian process
- support vector
- learning problems
- continuous functions
- geodesic distance
- dimensionality reduction
- knn
- manifold learning
- active learning