Bayesian Sparse Tucker Models for Dimension Reduction and Tensor Completion

10 May 2015Qibin ZhaoLiqing ZhangAndrzej Cichocki

Tucker decomposition is the cornerstone of modern machine learning on tensorial data analysis, which have attracted considerable attention for multiway feature extraction, compressive sensing, and tensor completion. The most challenging problem is related to determination of model complexity (i.e., multilinear rank), especially when noise and missing data are present... (read more)

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