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Bayesian Robust Tensor Factorization for Incomplete Multiway Data
Qibin Zhao, Guoxu Zhou, Liqing Zhang +2
We propose a generative model for robust tensor factorization in the presence of both missing data and outliers. The objective is to explicitly infer the underlying low-CP-rank ten…
Efficient Nonnegative Tucker Decompositions: Algorithms and Uniqueness
Guoxu Zhou, Andrzej Cichocki, Qibin Zhao +1
Nonnegative Tucker decomposition (NTD) is a powerful tool for the extraction of nonnegative parts-based and physically meaningful latent components from high-dimensional tensor dat…
Tensor Decompositions for Signal Processing Applications From Two-way to Multiway Component Analysis
A. Cichocki, D. Mandic, A-H. Phan +4
The widespread use of multi-sensor technology and the emergence of big datasets has highlighted the limitations of standard flat-view matrix models and the necessity to move toward…
Bayesian CP Factorization of Incomplete Tensors with Automatic Rank Determination
Qibin Zhao, Liqing Zhang, Andrzej Cichocki
CANDECOMP/PARAFAC (CP) tensor factorization of incomplete data is a powerful technique for tensor completion through explicitly capturing the multilinear latent factors. The existi…