Subspace Embeddings Under Nonlinear Transformations.
Aarshvi GajjarCameron MuscoPublished in: CoRR (2020)
Keyphrases
- low dimensional
- kernel based nonlinear
- high dimensional data
- dimensionality reduction
- hilbert space
- high dimensional
- kernel pca
- subspace clustering
- principal component analysis
- linear dimensionality reduction
- vector space
- subspace learning
- lower dimensional
- manifold learning
- kernel principal component analysis
- subspace methods
- discriminant subspace
- euclidean space
- principal components
- dimension reduction
- image transformations
- high dimensional feature space
- feature space
- similarity measure
- clustering high dimensional data
- face recognition
- independent component analysis
- high order
- semi supervised
- data points
- subspace clusters
- low dimensional spaces
- feature extraction