75 citations · 81 across the 3 of their papers we have counts for
3 papers
cs.IR2021★ 3 cited
Evaluating Music Recommendations with Binary Feedback for Multiple Stakeholders
Sasha Stoikov, Hongyi Wen
High quality user feedback data is essential to training and evaluating a successful music recommendation system, particularly one that has to balance the needs of multiple stakeho…
cs.IR2021★ 3 cited
Correcting the User Feedback-Loop Bias for Recommendation Systems
Weishen Pan, Sen Cui, Hongyi Wen +3
Selection bias is prevalent in the data for training and evaluating recommendation systems with explicit feedback. For example, users tend to rate items they like. However, when ra…
cs.LG2020★ 75 cited
Revisiting Adversarially Learned Injection Attacks Against Recommender Systems
Jiaxi Tang, Hongyi Wen, Ke Wang
Recommender systems play an important role in modern information and e-commerce applications. While increasing research is dedicated to improving the relevance and diversity of the…