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Nonnegative matrix factorization

By: Gillis, Nicolas.

Series: Data science ; 2.Publisher: Philadelphia : Society for Industrial and Applied Mathematics, 2021Description: xxv, 350 p. ; ill. 26 cm.ISBN: 9781611976403.Subject(s): Algorithms | Data Science Data Analytics | Computer algorithms | Data mining | Non-negative matrices | Bolzano-Weierstress theorem | Condition number | Contact change point | Distributional robustness | Feature extraction | Hierarchical alternating least squares | Identifiability | Karush-Kuhn-Tucker (KKT) conditions | MATLAB | Minimum -volumeNMF | Near-separable factorization | Nested polytope problem | Nonnegative rank | Orthogonal NMF | Principal component analysis | Robust PCA | Thomas matrix | Verttex component analysis | High dimensional data setsDDC classification: 512.9434 Summary: This book provides a comprehensive and up-to-date account of the NMF problem and its most significant features.

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Item type	Current location	Call number	Status	Date due	Barcode
Books		512.9434 GIL (Browse shelf)	Available		033451

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Previous	512.9434 FAL Totally nonnegative matrices	512.9434 GAN Applications of the theory of matrices	512.9434 GEN Matrix algebra : theory, computations, and applications in statistics	512.9434 GIL Nonnegative matrix factorization	512.9434 GOL Matrices Moments and quadrature with applications	512.9434 GOL Matrix computations	512.9434 HAC Iterative solution of large sparse systems of equations	Next

Includes bibliographical references and index.

This book provides a comprehensive and up-to-date account of the NMF problem and its most significant features.

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