On Inner-Product Kernels of High Dimensional Data.
Zhenyu LiaoRomain CouilletPublished in: CAMSAP (2019)
Keyphrases
- high dimensional data
- dimensionality reduction
- high dimensional
- low dimensional
- nearest neighbor
- high dimensionality
- data sets
- high dimensions
- data points
- data analysis
- feature space
- kernel function
- subspace clustering
- linear discriminant analysis
- similarity search
- dimension reduction
- kernel methods
- vector space
- manifold learning
- input space
- nonlinear dimensionality reduction
- original data
- low rank
- high dimensional data sets
- sparse representation
- clustering high dimensional data
- high dimensional datasets
- support vector
- database
- lower dimensional
- dimensional data
- neural network
- text data
- kernel machines
- high dimensional spaces
- subspace learning
- pattern recognition
- query processing
- clustering method
- euclidean distance