Linear Kernel Tests via Empirical Likelihood for High-Dimensional Data.
Lizhong DingZhi LiuYu LiShizhong LiaoYong LiuPeng YangGe YuLing ShaoXin GaoPublished in: AAAI (2019)
Keyphrases
- high dimensional data
- nearest neighbor
- low dimensional
- high dimensions
- dimensionality reduction
- high dimensional
- data sets
- subspace clustering
- high dimensionality
- data points
- data analysis
- manifold learning
- dimension reduction
- dimensional data
- nonlinear dimensionality reduction
- variable selection
- linear discriminant analysis
- original data
- input space
- data distribution
- similarity search
- complex data
- input data
- lower dimensional
- machine learning
- text data
- subspace learning
- high dimensional feature spaces
- high dimensional datasets
- clustering high dimensional data
- database
- small sample size
- high dimensional spaces
- sparse representation
- image processing
- locally linear embedding
- similarity measure