48 citations · 89 across the 4 of their papers we have counts for
4 papers
RESUS: Warm-Up Cold Users via Meta-Learning Residual User Preferences in CTR Prediction
Yanyan Shen, Lifan Zhao, Weiyu Cheng +3
Click-Through Rate (CTR) prediction on cold users is a challenging task in recommender systems. Recent researches have resorted to meta-learning to tackle the cold-user challenge,…
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…
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…
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…