Abstract: Matrix factorization is a central paradigm in matrix completion and collaborative filtering. Low-rank factorizations have been extremely successful in reconstructing and generalizing ...

Abstract: Simplex-structured matrix factorization (SSMF) is a common task encountered in signal processing and machine learning. Minimum-volume constrained unmixing (MVCU) algorithms are among the ...

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Extreme Scale DuaLip is specifically developed to tackle problems arising in web applications that usually have hundreds of millions of users and millions of items, pushing the number of optimization ...

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