2 papers
cs.LG2023
Geometry-Calibrated DRO: Combating Over-Pessimism with Free Energy Implications
Jiashuo Liu, Jiayun Wu, Tianyu Wang +3
Machine learning algorithms minimizing average risk are susceptible to distributional shifts. Distributionally Robust Optimization (DRO) addresses this issue by optimizing the wors…
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…