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Efficient and Distributed Algorithms for Large-Scale Generalized Canonical Correlations Analysis.

, , , , , , , and . ICDM, page 871-876. IEEE Computer Society, (2016)

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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)Nonnegative Matrix Factorization for Signal and Data Analytics: Identifiability, Algorithms, and Applications., , , and . IEEE Signal Process. Mag., 36 (2): 59-80 (2019)Learning Nonlinear Mixtures: Identifiability and Algorithm., , , and . CoRR, (2019)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)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)An adaptive machine learning algorithm for the resource-constrained classification problem., , , , and . Eng. Appl. Artif. Intell., (March 2023)Kullback-Leibler principal component for tensors is not NP-hard., and . ACSSC, page 693-697. IEEE, (2017)