Tensor-Train Parameterization for Ultra Dimensionality Reduction.
Mingyuan BaiS. T. Boris ChoyXin SongJunbin GaoPublished in: ICBK (2019)
Keyphrases
- dimensionality reduction
- high dimensional data
- low dimensional
- pattern recognition
- high dimensional
- principal component analysis
- feature selection
- feature extraction
- high dimensionality
- data representation
- singular value decomposition
- data points
- subspace learning
- lower dimensional
- high speed
- neighborhood preserving embedding
- random projections
- principal components
- supervised dimensionality reduction
- pattern recognition and machine learning
- manifold learning
- higher order tensors
- euclidean distance
- linear dimensionality reduction
- sparse representation
- feature space
- dimensionality reduction methods
- locality preserving projections
- machine learning
- face recognition
- linear discriminant analysis
- high order
- kernel pca
- linear transformation
- structure preserving
- semi supervised dimensionality reduction
- nonlinear dimensionality reduction
- metric learning
- support vector machine