1 code implementation • 30 Oct 2023 • Ziqian Lin, Hao Ding, Nghia Trong Hoang, Branislav Kveton, Anoop Deoras, Hao Wang
In particular, we propose to develop a generic recommender that captures universal interaction patterns by training on generic user-item interaction data extracted from different domains, which can then be fast adapted to improve few-shot learning performance in unseen new domains (with limited data).