A novel estimation procedure for robust CP model fitting

The usual way of parameter estimation in CANDECOM/PARAFAC (CP) is an alternating least squares (ALS) procedure that yields least-squares so- lutions and provides consistent outcomes but at the same time has several deficien- cies, like sensitivity to the presence of outliers in the data, slow convergence, and susceptibility to degeneracy conditions. A number of works have addressed these weaknesses, but to our knowledge, there is no outlier-robust procedure that is hi- ghly computationally efficient at the same time, especially for large data sets. We propose a robust procedure based on an integrated estimation algorithm, alternative to ALS, which guards against outliers and is computationally efficient at the same time.