Le Thi Hoai An, Tao Pham Dinh, Xuan Thanh Vo: DC Programming and DCA for Nonnegative Matrix Factorization.

Abstract: Techniques of matrix factorization or decomposition always play a central role in numerical analysis and statistics with many applications in real-world problems. Recently, the NMF dimension-reduction technique, popularized by Lee and Seung with their multiplicative update algorithm (an adapted gradient approach) has drawn much attention of researchers and practitioners. Since many of existing algorithms lack a firm theoretical foundation, and designing efficient scalable algorithms for NMF still is a challenging problem, we investigate DC programming and DCA for NMF.


Keywords: Nonnegative matrix factorization, Multiplicative update algorithm, DC programming, DCA.



Citation: Le Thi Hoai An, Tao Pham Dinh, Xuan Thanh Vo: DC Programming and DCA for Nonnegative Matrix Factorization. In Dosam Hwang, Jason J. Jung, Ngoc Thanh Nguyen (Eds.): Computational Collective Intelligence. Technologies and Applications, Lecture Notes in Computer Science ISBN, 978-3-319-11288-6: 573-582, Springer 2014.


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