Boolean matrix factorization via nonnegative auxiliary optimization

HIGHLIGHTS

  • who: . and collaborators from the Computer, Computational and Statistics Division, Los Alamos National Laboratory, USA have published the article: Boolean Matrix Factorization via Nonnegative Auxiliary Optimization, in the Journal: (JOURNAL)
  • what: The authors provide the proofs for the equivalencies of the two solution spaces under the existence of an exact solution. The authors propose a new algorithm for BMF, the authors call Boolean Auxiliary Non-negative Matrix Factorization (BANMF). The authors demonstrate that BANMF method outperforms other state-of-the-art methods for the BMF problem when there exists a discrepancy between the nonnegative and . . .

     

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