Accelerating block coordinate descent for nonnegative tensor factorization
International audienceThis paper is concerned with improving the empirical convergence speed of block-coordinate descent algorithms for approximate nonnegative tensor factorization (NTF).
Nicolas Gillis +2 more
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Hyperspectral Unmixing via Total Variation Regularized Nonnegative Tensor Factorization
Hyperspectral unmixing decomposes a hyperspectral imagery (HSI) into a number of constituent materials and associated proportions. Recently, nonnegative tensor factorization (NTF)-based methods have been proposed for hyperspectral unmixing thanks to ...
Yuan Yan Tang, Yuntao Qian
exaly +2 more sources
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Seeking an appropriate alternative least squares algorithm for nonnegative tensor factorizations
Neural Computing and Applications, 2011Alternative least squares (ALS) algorithm is considered as a “work-horse” algorithm for general tensor factorizations. A common form of this algorithm for nonnegative tensor factorizations (NTF) is always combined with a nonlinear projection (rectifier) to enforce nonnegative entries during the estimation.
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Matrix-Vector Nonnegative Tensor Factorization for Blind Unmixing of Hyperspectral Imagery
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