Current Research
Current research in nonnegative matrix factorization includes, but not limited to,
(1) Algorithmic: searching for global minima of the factors and factor initialization.
(2) Scalability: how to factorize million-by-billion matrices, which are commonplace in Web-scale data mining, e.g., see Distributed Nonnegative Matrix Factorization (DNMF)
(3) Online: how to update the factorization when new data comes in without recomputing from scratch.
Read more about this topic: Non-negative Matrix Factorization
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