Tensor Sparse Coding for Positive Definite Matrices.

  title={Tensor Sparse Coding for Positive Definite Matrices.},
  author={Ravishankar Sivalingam and Daniel Boley and Vassilios Morellas and Nikos Papanikolopoulos},
  journal={IEEE transactions on pattern analysis and machine intelligence},
In recent years, there has been extensive research on sparse representation of vector-valued signals. In the matrix case, the data points are merely vectorized and treated as vectors thereafter (for e.g., image patches). However, this approach cannot be used for all matrices, as it may destroy the inherent structure of the data. Symmetric positive definite (SPD) matrices constitute one such class of signals, where their implicit structure of positive eigenvalues is lost upon vectorization. This… CONTINUE READING
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