Attention-driven Tree-structured Convolutional LSTM for High Dimensional Data Understanding.
Bin KongXin WangJunjie BaiYi LuFeng GaoKunlin CaoQi SongShaoting ZhangSiwei LyuYoubing YinPublished in: CoRR (2019)
Keyphrases
- high dimensional data
- dimensionality reduction
- low dimensional
- nearest neighbor
- high dimensional
- high dimensions
- high dimensionality
- data sets
- similarity search
- data points
- subspace clustering
- input space
- manifold learning
- original data
- data analysis
- high dimensional spaces
- dimension reduction
- high dimensional data sets
- sparse representation
- linear discriminant analysis
- tree structure
- text data
- data distribution
- nonlinear dimensionality reduction
- dimensional data
- high dimensional datasets
- clustering high dimensional data
- small sample size
- regression problems
- lower dimensional
- query processing
- structured data
- spectral clustering