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Nonnegative Matrix Factorization for Signal and Data Analytics: Identifiability, Algorithms, and Applications.

, , , and . CoRR, (2018)

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On Identifiability of Nonnegative Matrix Factorization., , and . CoRR, (2017)A Flexible and Efficient Algorithmic Framework for Constrained Matrix and Tensor Factorization., , and . CoRR, (2015)Learning Nonlinear Mixtures: Identifiability and Algorithm., , , and . CoRR, (2019)Nonnegative Matrix Factorization for Signal and Data Analytics: Identifiability, Algorithms, and Applications., , , and . IEEE Signal Process. Mag., 36 (2): 59-80 (2019)Feasible Point Pursuit and Successive Approximation of Non-Convex QCQPs., , , , and . IEEE Signal Process. Lett., 22 (7): 804-808 (2015)On Identifiability of Nonnegative Matrix Factorization., , and . IEEE Signal Process. Lett., 25 (3): 328-332 (2018)Consensus-ADMM for General Quadratically Constrained Quadratic Programming., and . IEEE Trans. Signal Process., 64 (20): 5297-5310 (2016)Block-randomized Stochastic Proximal Gradient for Constrained Low-rank Tensor Factorization., , , and . ICASSP, page 7485-7489. IEEE, (2019)An adaptive machine learning algorithm for the resource-constrained classification problem., , , , and . Eng. Appl. Artif. Intell., (March 2023)Translation Invariant Word Embeddings., , , , , , , and . EMNLP, page 1084-1088. The Association for Computational Linguistics, (2015)