4 papers
Creator-Side Recommender System: Challenges, Designs, and Applications
Xiaoshuang Chen, Yibo Wang, Yao Wang +4
Users and creators are two crucial components of recommender systems. Typical recommender systems focus on the user side, providing the most suitable items based on each user's req…
RPAF: A Reinforcement Prediction-Allocation Framework for Cache Allocation in Large-Scale Recommender Systems
Shuo Su, Xiaoshuang Chen, Yao Wang +5
Modern recommender systems are built upon computation-intensive infrastructure, and it is challenging to perform real-time computation for each request, especially in peak periods,…
Cache-Aware Reinforcement Learning in Large-Scale Recommender Systems
Xiaoshuang Chen, Gengrui Zhang, Yao Wang +4
Modern large-scale recommender systems are built upon computation-intensive infrastructure and usually suffer from a huge difference in traffic between peak and off-peak periods. I…
UNEX-RL: Reinforcing Long-Term Rewards in Multi-Stage Recommender Systems with UNidirectional EXecution
Gengrui Zhang, Yao Wang, Xiaoshuang Chen +3
In recent years, there has been a growing interest in utilizing reinforcement learning (RL) to optimize long-term rewards in recommender systems. Since industrial recommender syste…