54 citations · 63 across the 6 of their papers we have counts for
6 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 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…
Item Cold Start Recommendation via Adversarial Variational Auto-encoder Warm-up
Shenzheng Zhang, Qi Tan, Xinzhi Zheng +2
The gap between the randomly initialized item ID embedding and the well-trained warm item ID embedding makes the cold items hard to suit the recommendation system, which is trained…
Slate-Aware Ranking for Recommendation
Yi Ren, Xiao Han, Xu Zhao +2
We see widespread adoption of slate recommender systems, where an ordered item list is fed to the user based on the user interests and items' content. For each recommendation, the…
Improving Item Cold-start Recommendation via Model-agnostic Conditional Variational Autoencoder
Xu Zhao, Yi Ren, Ying Du +2
Embedding & MLP has become a paradigm for modern large-scale recommendation system. However, this paradigm suffers from the cold-start problem which will seriously compromise the e…
MIC: Model-agnostic Integrated Cross-channel Recommenders
Yujie Lu, Ping Nie, Shengyu Zhang +4
Semantically connecting users and items is a fundamental problem for the matching stage of an industrial recommender system. Recent advances in this topic are based on multi-channe…