Subspace Embeddings for the Polynomial Kernel.
Haim AvronHuy L. NguyenDavid P. WoodruffPublished in: NIPS (2014)
Keyphrases
- polynomial kernels
- low dimensional
- feature space
- dimensionality reduction
- high dimensional feature space
- kernel function
- gaussian kernels
- high dimensional data
- high dimensional
- support vector machine
- linearly separable
- support vector
- manifold learning
- principal component analysis
- input space
- euclidean space
- lower dimensional
- data points
- vector space
- finite sets
- feature extraction
- kernel pca
- binary classification
- euclidean distance
- distance measure
- data sets