Bayesian Robust Tensor Factorization for Incomplete Multiway Data

9 Oct 2014Qibin ZhaoGuoxu ZhouLiqing ZhangAndrzej CichockiShun-ichi Amari

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 tensor capturing the global information and a sparse tensor capturing the local information (also considered as outliers), thus providing the robust predictive distribution over missing entries... (read more)

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