On Intrinsic Cramér-Rao Bounds for Riemannian Submanifolds and Quotient Manifolds.
Nicolas BoumalPublished in: IEEE Trans. Signal Process. (2013)
Keyphrases
- manifold learning
- low dimensional
- riemannian manifolds
- geometric structure
- lie group
- euclidean space
- information geometry
- upper bound
- geodesic distance
- high dimensional
- lower bound
- tangent space
- vector space
- dimensionality reduction
- error bounds
- fisher information
- geodesic paths
- underlying manifold
- machine intelligence
- arbitrary dimension
- rao bound
- lower and upper bounds
- dimension reduction
- data points
- shape analysis
- parameter space
- high dimensional data
- feature space
- feature selection
- higher dimensional
- endpoints
- linear subspace
- euclidean metric
- semi supervised
- feature extraction