Algorithms for an Efficient Tensor Biclustering

@inproceedings{Faneva2019AlgorithmsFA,
  title={Algorithms for an Efficient Tensor Biclustering},
  author={Andriantsiory Dina Faneva and Mustapha Lebbah and Hanene Azzag and Ga{\"e}l Beck},
  booktitle={PAKDD},
  year={2019}
}
Consider a data set collected by (individuals-features) pairs in different times. It can be represented as a tensor of three dimensions (Individuals, features and times). The tensor biclustering problem computes a subset of individuals and a subset of features whose signal trajectories over time lie in a low-dimensional subspace, modeling similarity among the signal trajectories while allowing different scalings across different individuals or different features. This approach are based on… 
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Multi-Slice Clustering for 3-order Tensor Data
TLDR
This work proposes a new method, namely the multi-slice clustering (MSC) for a 3-order tensor data set, which defines a similarity measure between matrix slices up to a threshold (precision) parameter, and from that, identifies a cluster.

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