Tensor Networks for Dimensionality Reduction and Large-Scale Optimizations. Part 2 Applications and Future Perspectives.
Andrzej CichockiAnh Huy PhanQibin ZhaoNamgil LeeIvan V. OseledetsMasashi SugiyamaDanilo P. MandicPublished in: CoRR (2017)
Keyphrases
- dimensionality reduction
- high dimensional data
- pattern recognition
- high dimensional
- data representation
- feature extraction
- principal component analysis
- real world
- high dimensionality
- data points
- feature space
- feature selection
- small scale
- pattern recognition and machine learning
- current issues
- network structure
- random projections
- manifold learning
- heterogeneous networks
- structure preserving
- subspace learning
- lower dimensional
- social networks
- computer networks
- linear discriminant analysis
- principal components
- network design
- complex networks
- low dimensional
- least squares
- long term