MULTIPAR: Supervised Irregular Tensor Factorization with Multi-task Learning. (arXiv:2208.00993v2 [cs.LG] UPDATED)

Tensor factorization has received increasing interest due to its intrinsic
ability to capture latent factors in multi-dimensional data with many
applications such as recommender systems and Electronic Health Records (EHR)
mining. PARAFAC2 and its variants have been proposed to address irregular
tensors where one of the tensor modes is not aligned, e.g., different users in
recommender systems or patients in EHRs may have different length of records.
PARAFAC2 has been successfully applied on EHRs for extracting meaningful
medical concepts (phenotypes). …

arxiv factorization learning lg multi-task learning tensor