Accelerating the Lee-Seung Algorithm for Nonnegative Matrix Factorization
Date
2005-03
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Abstract
Approximate nonnegative matrix factorization is an emerging technique with a wide spectrum of potential applications in data analysis. Currently, the most-used algorithms for this problem are those proposed by Lee and Seung. In this paper we present a variation of one of the Lee-Seung algorithms with a notably improved performance. We also show that algorithms of this type do not necessarily converge to local minima.
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Technical report
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Citation
Gonzalez, Edward F. and Zhang, Yin. "Accelerating the Lee-Seung Algorithm for Nonnegative Matrix Factorization." (2005) https://hdl.handle.net/1911/102034.