• Corpus ID: 125837025

Tensor Valued Common and Individual Feature Extraction: Multi-dimensional Perspective

@article{Kisil2017TensorVC,
  title={Tensor Valued Common and Individual Feature Extraction: Multi-dimensional Perspective},
  author={Ilia Kisil and Giuseppe Giovanni Calvi and Danilo P. Mandic},
  journal={arXiv: Signal Processing},
  year={2017}
}
A novel method for common and individual feature analysis from exceedingly large-scale data is proposed, in order to ensure the tractability of both the computation and storage and thus mitigate the curse of dimensionality, a major bottleneck in modern data science. This is achieved by making use of the inherent redundancy in so-called multi-block data structures, which represent multiple observations of the same phenomenon taken at different times, angles or recording conditions. Upon… 
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