Computation in Low-Dimensional Geometry and Topology (Dagstuhl Seminar 19352).
Maarten LöfflerAnna LubiwSaul SchleimerErin Wolf ChambersPublished in: Dagstuhl Reports (2019)
Keyphrases
- low dimensional
- high dimensional
- dimension reduction
- high dimensional data
- linear subspace
- underlying manifold
- dimensionality reduction
- manifold learning
- efficient computation
- three dimensional
- low dimensional manifolds
- topological information
- principal component analysis
- vector space
- persistent homology
- data sets
- geometric constraints
- nearest neighbor
- d objects
- feature space
- neural network