29 citations · 52 across the 5 of their papers we have counts for
3 papers · 1 filter
Improving Multi-Task Generalization via Regularizing Spurious Correlation
Ziniu Hu, Zhe Zhao, Xinyang Yi +4
Multi-Task Learning (MTL) is a powerful learning paradigm to improve generalization performance via knowledge sharing. However, existing studies find that MTL could sometimes hurt…
Learning to Embed Categorical Features without Embedding Tables for Recommendation
Wang-Cheng Kang, Derek Zhiyuan Cheng, Tiansheng Yao +4
Embedding learning of categorical features (e.g. user/item IDs) is at the core of various recommendation models including matrix factorization and neural collaborative filtering. T…
Self-supervised Learning for Large-scale Item Recommendations
Tiansheng Yao, Xinyang Yi, Derek Zhiyuan Cheng +8
Large scale recommender models find most relevant items from huge catalogs, and they play a critical role in modern search and recommendation systems. To model the input space with…