9 citations · 16 across the 4 of their papers we have counts for
4 papers
Disentangled Counterfactual Reasoning for Unbiased Sequential Recommendation
Yi Ren, Xu Zhao, Hongyan Tang +1
Sequential recommender systems have achieved state-of-the-art recommendation performance by modeling the sequential dynamics of user activities. However, in most recommendation sce…
Unbiased Pairwise Learning from Implicit Feedback for Recommender Systems without Biased Variance Control
Yi Ren, Hongyan Tang, Jiangpeng Rong +1
Generally speaking, the model training for recommender systems can be based on two types of data, namely explicit feedback and implicit feedback. Moreover, because of its general a…
Unbiased Learning to Rank with Biased Continuous Feedback
Yi Ren, Hongyan Tang, Siwen Zhu
It is a well-known challenge to learn an unbiased ranker with biased feedback. Unbiased learning-to-rank(LTR) algorithms, which are verified to model the relative relevance accurat…
Unbiased Pairwise Learning to Rank in Recommender Systems
Yi Ren, Hongyan Tang, Siwen Zhu
Nowadays, recommender systems already impact almost every facet of peoples lives. To provide personalized high quality recommendation results, conventional systems usually train po…