2 citations · 7 across the 5 of their papers we have counts for
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cs.IR2022
Debiased Recommendation with User Feature Balancing
Mengyue Yang, Guohao Cai, Furui Liu +5
Debiased recommendation has recently attracted increasing attention from both industry and academic communities. Traditional models mostly rely on the inverse propensity score (IPS…
cs.IR2021★ 2 cited
Top-N Recommendation with Counterfactual User Preference Simulation
Mengyue Yang, Quanyu Dai, Zhenhua Dong +3
Top-N recommendation, which aims to learn user ranking-based preference, has long been a fundamental problem in a wide range of applications. Traditional models usually motivate th…
cs.IR2021★ 2 cited
CMML: Contextual Modulation Meta Learning for Cold-Start Recommendation
Xidong Feng, Chen Chen, Dong Li +3
Practical recommender systems experience a cold-start problem when observed user-item interactions in the history are insufficient. Meta learning, especially gradient based one, ca…