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Leveraging Joint-Diagonalization in Transform-Learning NMF [PDF]
IEEE Transactions on Signal Processing, 2022 International audienceNon-negative matrix factorization with transform learning (TL-NMF) is a recent idea that aims at learning data representations suited to NMF. In this work, we relate TL-NMF to the classical matrix joint-diagonalization (JD) problem.
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