Generalized User Representations for Transfer Learning in Large-Scale Recommender Systems

The author presents a novel framework for user representation in large-scale recommender systems, combining representation learning and transfer learning to effectively capture diverse user tastes. The approach aims to reduce infrastructure costs while showcasing remarkable efficacy across multiple evaluation tasks.