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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 ...
Abstract: Nonnegative matrix factorization (NMF) is a powerful tool for signal processing and machine learning. Geometrically, it can be interpreted as the problem of finding a conic hull, which ...
A comprehensive implementation of various Matrix Decomposition Techniques from the lens of Linear Algebra to produce efficient computing of SVD, PCA, Feature Selection & Data Analysis in Python. To ...
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