Deep Reinforcement Learning for Recommender Systems
Papers
Recommender Systems:
β SIGIR 20 Neural Interactive Collaborative Filtering paper code
β KDD 20 Jointly Learning to Recommend and Advertise paper
β CIKM 20 Whole-Chain Recommendations paper
β KDD 19 Reinforcement Learning to Optimize Long-term User Engagement in Recommender Systems paper
β DSFAA 19 Reinforcement Learning to Diversify Top-N Recommendation paper code
β KDD 18 Recommendations with Negative Feedback via Pairwise Deep Reinforcement Learning paper
β RecSys 18 Deep Reinforcement Learning for Page-wise Recommendations paper
β DRL4KDD Deep Reinforcement Learning for List-wise Recommendations paper
β Sigweb 19 Deep Reinforcement Learning for Search, Recommendation, and Online Advertising: A Survey paper
β Arxiv 19 Model-Based Reinforcement Learning for Whole-Chain Recommendations paper
β Arxiv 19 Simulating User Feedback for Reinforcement Learning Based Recommendations paper
β Arxiv 19 Deep Reinforcement Learning for Online Advertising in Recommender Systems paper
Search Engine:
β KDD 18 Reinforcement Learning to Rank in E-Commerce Search Engine Formalization, Analysis, and Application paper
Advertisement
β Arxiv 19 Deep Reinforcement Learning for Online Advertising in Recommender Systems paper
Re-ranking (Top K):
β IJCAI 19 Reinforcement Learning for Slate-based Recommender Systems: A Tractable Decomposition and Practical Methodology paper arxiv
β Arixv 19 Seq2Slate: Re-ranking and Slate Optimization with RNNs paper
β KDD 19 Exact-K Recommendation via Maximal Clique Optimization paper
β WWW 19 Value-aware Recommendation based on Reinforcement Profit Maximization paper code Dataset
Bandit:
β WWW 10 A Contextual-Bandit Approach to Personalized News Article Recommendation paper
β KDD 16 Online Context-Aware Recommendation with Time Varying Multi-Armed Bandit paper
β CIKM 17 Returning is Believing Optimizing Long-term User Engagement in Recommender Systems
β ICLR 18 Deep Learning with Logged Bandit Feedback paper
β Recsys 18 Explore, Exploit, and Explain Personalizing Explainable Recommendations with Bandits paper
Hierarchical RL
β AAAI19 Hierarchical Reinforcement Learning for Course Recommendation in MOOCs paper
β WWW 19 Aggregating E-commerce Search Results from Heterogeneous Sources via Hierarchical Reinforcement Learning paper
DQN:
β WWW 18 DRN: A Deep Reinforcement Learning Framework for News Recommendation paper
β KDD 18 Stabilizing Reinforcement Learning in Dynamic Environment with Application to Online Recommendation paper
β ICML 19 Off-Policy Deep Reinforcement Learning without Exploration paper
Policy Gradient:
β WSDM 19 Top-K Off-Policy Correction for a REINFORCE Recommender System paper
β NIPS 17 Off-policy evaluation for slate recommendation paper
β ICML 19 Safe Policy Improvement with Baseline Bootstrapping paper
β WWW 19 Policy Gradients for Contextual Recommendations paper
β AAAI 19 Large-scale Interactive Recommendation with Tree-structured Policy Gradient paper
Actor-Critic:
β Arxiv 15 Deep Reinforcement Learning in Large Discrete Action Spaces paper code
β Arxiv 18 Deep Reinforcement Learning based Recommendation with Explicit User-Item Interactions Modeling paper
β KDD 18 Supervised Reinforcement Learning with Recurrent Neural Network for Dynamic Treatment Recommendation paper
Multi-agent:
β WWW 18 Learning to Collaborate Multi-Scenario Ranking via Multi-Agent Reinforcement Learning paper
Offline:
β WSDM 19 Offline Evaluation to Make Decisions About Playlist Recommendation Algorithms paper
β KDD 19 Off-policy Learning for Multiple Loggers paper
Explainable:
β ICDM 18 A Reinforcement Learning Framework for Explainable Recommendation paper
β SIGIR 19 Reinforcement Knowledge Graph Reasoning for Explainable Recommendation paper
Simulation:
β ICML 19 Generative Adversarial User Model for Reinforcement Learning Based Recommendation System paper