74 citations · 200 across the 11 of their papers we have counts for
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cs.IR2022★ 1 cited
Boosting Factorization Machines via Saliency-Guided Mixup
Chenwang Wu, Defu Lian, Yong Ge +3
Factorization machines (FMs) are widely used in recommender systems due to their adaptability and ability to learn from sparse data. However, for the ubiquitous non-interactive fea…
cs.IR2019★ 23 cited
Binarized Collaborative Filtering with Distilling Graph Convolutional Networks
Haoyu Wang, Defu Lian, Yong Ge
The efficiency of top-K item recommendation based on implicit feedback are vital to recommender systems in real world, but it is very challenging due to the lack of negative sample…
cs.IR2019
Personalized Multimedia Item and Key Frame Recommendation
Le Wu, Lei Chen, Yonghui Yang +4
When recommending or advertising items to users, an emerging trend is to present each multimedia item with a key frame image (e.g., the poster of a movie). As each multimedia item…