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In this paper we propose new algorithms for 3D tensor decomposition/factorization with many potential applications, especially in multi-way Blind Source Separation (BSS), multidimensional data analysis, and sparse signal/image representations. We derive and compare three classes of algorithms: Multiplicative, Fixed-Point Alternating Least Squares (FPALS) and Alternating Interior-Point Gradient (AIPG) algorithms. Some of the proposed algorithms are characterized by improved robustness,doi:10.1109/icassp.2007.367106 dblp:conf/icassp/CichockiZCPA07 fatcat:jgl7krnhtba3rbie3j63hn63zu