48 citations · 84 across the 6 of their papers we have counts for
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cs.LG2020★ 20 cited
Differentiable Neural Input Search for Recommender Systems
Weiyu Cheng, Yanyan Shen, Linpeng Huang
Latent factor models are the driving forces of the state-of-the-art recommender systems, with an important insight of vectorizing raw input features into dense embeddings. The dime…
cs.LG2019★ 10 cited
Adaptive Factorization Network: Learning Adaptive-Order Feature Interactions
Weiyu Cheng, Yanyan Shen, Linpeng Huang
Various factorization-based methods have been proposed to leverage second-order, or higher-order cross features for boosting the performance of predictive models. They generally en…
cs.LG2018★ 48 cited
Explaining Latent Factor Models for Recommendation with Influence Functions
Weiyu Cheng, Yanyan Shen, Yanmin Zhu +1
Latent factor models (LFMs) such as matrix factorization achieve the state-of-the-art performance among various Collaborative Filtering (CF) approaches for recommendation. Despite…