49 citations · 49 across the 3 of their papers we have counts for
3 papers
cs.IR2023
Exploring and Exploiting Data Heterogeneity in Recommendation
Zimu Wang, Jiashuo Liu, Hao Zou +4
Massive amounts of data are the foundation of data-driven recommendation models. As an inherent nature of big data, data heterogeneity widely exists in real-world recommendation sy…
cs.LG2023
Gradient Norm Aware Minimization Seeks First-Order Flatness and Improves Generalization
Xingxuan Zhang, Renzhe Xu, Han Yu +2
Recently, flat minima are proven to be effective for improving generalization and sharpness-aware minimization (SAM) achieves state-of-the-art performance. Yet the current definiti…
cs.LG2022★ 49 cited
CausPref: Causal Preference Learning for Out-of-Distribution Recommendation
Yue He, Zimu Wang, Peng Cui +4
In spite of the tremendous development of recommender system owing to the progressive capability of machine learning recently, the current recommender system is still vulnerable to…