Variational Regularized 2-D Nonnegative Matrix Factorization

@article{Gao2012VariationalR2,
  title={Variational Regularized 2-D Nonnegative Matrix Factorization},
  author={Bin Gao and Wai lok Woo and Satnam Singh Dlay},
  journal={IEEE Transactions on Neural Networks and Learning Systems},
  year={2012},
  volume={23},
  pages={703-716}
}
A novel approach for adaptive regularization of 2-D nonnegative matrix factorization is presented. The proposed matrix factorization is developed under the framework of maximum a posteriori probability and is adaptively fine-tuned using the variational approach. The method enables: (1) a generalized criterion for variable sparseness to be imposed onto the solution; and (2) prior information to be explicitly incorporated into the basis features. The method is computationally efficient and has… CONTINUE READING

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