Nonnegative Matrix Factorization Using ADMM

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The Nonnegative Matrix Factorization Using ADMM is a method that is used to factor matrices into nonnegative matrices. This method is particularly useful when dealing with data that has nonnegative properties. The ADMM algorithm is used to solve the optimization problem that arises when performing this factorization. Additionally, this method can be applied to a variety of fields, including signal processing, image processing, and data analysis. By using the Nonnegative Matrix Factorization Using ADMM, researchers can better understand the underlying structure of their data and make more informed decisions based on their findings.