Censored Least Squares for Imputing Missing Values in PARAFAC Tensor Factorization
Ethan C. Hung,
Enio Hodzic,
Zhixin Cyrillus Tan
et al.
Abstract:Tensor factorization is a dimensionality reduction method applied to multidimensional arrays. These methods are useful for identifying patterns within a variety of biomedical datasets due to their ability to preserve the organizational structure of experiments and therefore aid in generating meaningful insights. However, missing data in the datasets being analyzed can impose challenges. Tensor factorization can be performed with some level of missing data and reconstruct a complete tensor. However, while tenso… Show more
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