Two heuristic algorithms (fixed-point from penalized KKT and staged ADAM) are proposed for symmetric multi-type orthogonal NMF tri-factorization and evaluated on synthetic noisy data and citation networks for recovery and downstream tasks.
Neural Computation 19(10), 2756–2779 (2007)
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GNRBMF extends NRBMF by adding graph Laplacian regularization on the coefficient matrix to encourage similar representations for nearby samples while retaining non-negativity in the reduced biquaternion domain.
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Graph Regularized Non-negative Reduced Biquaternion Matrix Factorization for Color Image Recognition
GNRBMF extends NRBMF by adding graph Laplacian regularization on the coefficient matrix to encourage similar representations for nearby samples while retaining non-negativity in the reduced biquaternion domain.