1 code implementation • 2 May 2024 • Tianhao Shi, Yang Zhang, Jizhi Zhang, Fuli Feng, Xiangnan He
To this end, we propose Distributionally Robust Fair Optimization (DRFO), which minimizes the worst-case unfairness over all potential probability distributions of missing sensitive attributes instead of the reconstructed one to account for the impact of the reconstruction errors.
no code implementations • 8 Apr 2024 • Heyuan Li, Ce Chen, Tianhao Shi, Yuda Qiu, Sizhe An, GuanYing Chen, Xiaoguang Han
We further introduce a view-image consistency loss for the discriminator to emphasize the correspondence of the camera parameters and the images.
no code implementations • 25 Dec 2023 • Tianhao Shi, Yang Zhang, Zhijian Xu, Chong Chen, Fuli Feng, Xiangnan He, Qi Tian
Rather than directly dismissing the role of incremental learning, we ascribe this lack of anticipated performance improvement to the mismatch between the LLM4Recarchitecture and incremental learning: LLM4Rec employs a single adaptation module for learning recommendation, hampering its ability to simultaneously capture long-term and short-term user preferences in the incremental learning context.
1 code implementation • 26 Apr 2023 • Yang Zhang, Tianhao Shi, Fuli Feng, Wenjie Wang, Dingxian Wang, Xiangnan He, Yongdong Zhang
However, such a manner inevitably learns unstable feature interactions, i. e., the ones that exhibit strong correlations in historical data but generalize poorly for future serving.