An Evaluation Study of Generative Adversarial Networks for Collaborative Filtering

Fernando Benjamín Pérez Maurera, Maurizio Ferrari Dacrema, Paolo Cremonesi

This work explores the reproducibility of CFGAN. CFGAN and its family of models (TagRec, MTPR, and CRGAN) learn to generate personalized and fake-but-realistic rankings of preferen…