… matrix. … inal collective trace norm formulation of Singh and Gordon[16], Finally, the SVT
algorithm originally designed for a single matrix is extended to our collective matrix factorization …

… ] approach, in this work, we propose Coupled Entity Similarity (CES) to capture the explicit
… the coupling relationships for any entity type. • We present a unified framework of coupled …

… We propose a novel federated collective matrix factorization model. To keep the data local,
we improve the training strategy and the loss function. Specifically, we separate the training …

… Inspired by this idea, we introduce a collective Bayesian matrix factorization approach under
the conditions where sharing individual records across the data sites is not permitted, but …

… [24, 23] had also studied collective matrix factorization using a different matrix factorization
scheme … the collective factorization problem for one factor matrix at a time. Analysis of multiple …

… of matrices can be jointly analyzed using collective matrix … we introduce our coupled matrix
factorization model with … introduce our model for coupled matrix factorization (CMF) with …

… introduced a collective matrix factorization framework that simultaneously factorizes multiple
… fusion in metabolomics are variants of collective matrix factorization methods developed in …

… This work explores the ability of collective matrix factorization models in recommender
systems to make predictions about users and items for which there is side information available …

… source apportionment using a positive matrix factorization (PMF) model coupled with self-organizing …
The geo‑accumulation index (I geo ) and enrichment factor (EF) values collectively …

… Collective Matrix Factorization model called TSCMF for recommendation. We jointly factorize
the users’ rating information and social trust information in a collective matrix factorization …