39 citations · 48 across the 5 of their papers we have counts for
Showing 2020Show all
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cs.LG2020★ 5 cited
Offline Meta-level Model-based Reinforcement Learning Approach for Cold-Start Recommendation
Yanan Wang, Yong Ge, Li Li +2
Reinforcement learning (RL) has shown great promise in optimizing long-term user interest in recommender systems. However, existing RL-based recommendation methods need a large num…
cs.LG2020★ 2 cited
Developing Multi-Task Recommendations with Long-Term Rewards via Policy Distilled Reinforcement Learning
Xi Liu, Li Li, Ping-Chun Hsieh +3
With the explosive growth of online products and content, recommendation techniques have been considered as an effective tool to overcome information overload, improve user experie…