Tensor-Train Parameterization for Ultra Dimensionality Reduction.
Mingyuan BaiS. T. Boris ChoyXin SongJunbin GaoPublished in: CoRR (2019)
Keyphrases
- dimensionality reduction
- subspace learning
- principal component analysis
- high dimensional
- high dimensional data
- feature extraction
- high dimensionality
- feature space
- low dimensional
- random projections
- singular value decomposition
- pattern recognition
- high speed
- neighborhood preserving embedding
- dimensionality reduction methods
- feature selection
- supervised dimensionality reduction
- lower dimensional
- higher order tensors
- linear discriminant analysis
- data representation
- manifold learning
- principal components
- sparse representation
- pattern recognition and machine learning
- metric learning
- graph embedding
- neural network
- euclidean distance
- structure preserving
- locality preserving projections
- nonlinear dimensionality reduction
- locally linear embedding
- multidimensional scaling
- high order
- diffusion tensor