Abstract
This paper deals with coupled tensor factorization. A relaxed criterion derived from the advanced coupled matrix-tensor factorization (ACMTF) proposed by Acar et al. is described. The proposed relaxed ACMTF (RACMTF) criterion is based on weaker assumptions that are thus more often satisfied when dealing with actual data. Numerical simulations show the benefit of using jointly two data sets when the underlying factors are highly correlated, especially if one of the modality is less noisy than the other one. The proposed method is finally applied on actual Gaze&EEG data to estimate the ocular artifacts into the EEG recordings.
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