1 citations · 1 across the 2 of their papers we have counts for
5 papers
Should I send this notification? Optimizing push notifications decision making by modeling the future
Conor O'Brien, Huasen Wu, Shaodan Zhai +3
Most recommender systems are myopic, that is they optimize based on the immediate response of the user. This may be misaligned with the true objective, such as creating long term u…
Learning to Rank For Push Notifications Using Pairwise Expected Regret
Yuguang Yue, Yuanpu Xie, Huasen Wu +4
Listwise ranking losses have been widely studied in recommender systems. However, new paradigms of content consumption present new challenges for ranking methods. In this work we c…
A simple discriminative training method for machine translation with large-scale features
Tian Xia, Shaodan Zhai, Shaojun Wang
Margin infused relaxed algorithms (MIRAs) dominate model tuning in statistical machine translation in the case of large scale features, but also they are famous for the complexity…
Plackett-Luce model for learning-to-rank task
Tian Xia, Shaodan Zhai, Shaojun Wang
List-wise based learning to rank methods are generally supposed to have better performance than point- and pair-wise based. However, in real-world applications, state-of-the-art sy…
Analysis of Regression Tree Fitting Algorithms in Learning to Rank
Tian Xia, Shaodan Zhai, Shaojun Wang
In learning to rank area, industry-level applications have been dominated by gradient boosting framework, which fits a tree using least square error principle. While in classificat…