Gillis, Nicolas
Nonnegative matrix factorization
- Philadelphia : Society for Industrial and Applied Mathematics, 2021
- xxv, 350 p. ; ill. 26 cm
- Data science ; 2 .
Includes bibliographical references and index.
This book provides a comprehensive and up-to-date account of the NMF problem and its most significant features.
9781611976403
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 sets
512.9434 / GIL