A Perturbation Bound on the Subspace Estimator from Canonical Projections.
Karan SrivastavaDaniel L. Pimentel-AlarcónPublished in: CoRR (2022)
Keyphrases
- linear projection
- subspace projections
- estimation error
- lower bound
- dimensionality reduction
- upper bound
- least squares
- worst case
- subspace clustering
- low dimensional
- principal component analysis
- three dimensional
- cramer rao lower bound
- high dimensional
- maximum likelihood
- error estimation
- high dimensional data
- feature space
- projection matrix
- estimation algorithm
- kernel based nonlinear
- variance estimator
- polyhedral objects
- subspace learning
- error bounds
- radon transform
- data sets
- feature extraction
- maximum a posteriori
- discrete tomography
- optimization criterion
- linear subspace
- lower dimensional
- principal components
- subspace clusters
- confidence intervals
- subspace methods
- linear discriminant analysis
- perturbation method
- importance sampling
- feature selection