Add WSDM 2020 paper

README.md

@@ -32,6 +32,7 @@ Courses on Deep Reinforcement Learning (DRL) and DRL papers for recommender syst
 1. **Top-K Off-Policy Correction for a REINFORCE Recommender System**. Minmin Chen, Alex Beutel, Paul Covington, Sagar Jain, Francois Belletti, Ed H. Chi. WSDM 2019. [paper](https://arxiv.org/pdf/1812.02353.pdf)
 1. **Generative Adversarial User Model for Reinforcement Learning Based Recommendation System**. Xinshi Chen, Shuang Li, Hui Li, Shaohua Jiang, Yuan Qi, Le Song. ICML 2019. [paper](http://proceedings.mlr.press/v97/chen19f/chen19f.pdf)
 1. **Aggregating E-commerce Search Results from Heterogeneous Sources via Hierarchical Reinforcement Learning**. Ryuichi Takanobu, Tao Zhuang, Minlie Huang, Jun Feng, Haihong Tang, Bo Zheng. WWW 2019. [paper](https://arxiv.org/pdf/1902.08882.pdf)
+1. **Policy Gradients for Contextual Recommendations**. Feiyang Pan, Qingpeng Cai, Pingzhong Tang, Fuzhen Zhuang, Qing He. WWW 2019. [paper](https://arxiv.org/pdf/1802.04162.pdf)
 1. **Reinforcement Knowledge Graph Reasoning for Explainable Recommendation**. Yikun Xian, Zuohui Fu, S. Muthukrishnan, Gerard de Melo, Yongfeng Zhang. SIGIR 2019. [paper](http://yongfeng.me/attach/xian-sigir2019.pdf)
 1. **Reinforcement Learning to Optimize Long-term User Engagement in Recommender Systems**. Lixin Zou, Long Xia, Zhuoye Ding, Jiaxing Song, Weidong Liu, Dawei Yin. KDD 2019. [paper](https://arxiv.org/pdf/1902.05570.pdf)
 1. **Environment reconstruction with hidden confounders for reinforcement learning based recommendation**. Wenjie Shang, Yang Yu, Qingyang Li, Zhiwei Qin, Yiping Meng, Jieping Ye. KDD 2019. [paper](http://lamda.nju.edu.cn/yuy/GetFile.aspx?File=papers/kdd19-confounder.pdf)
@@ -41,7 +42,9 @@ Courses on Deep Reinforcement Learning (DRL) and DRL papers for recommender syst
 1. **Virtual-Taobao: Virtualizing real-world online retail environment for reinforcement learning**. Jing-Cheng Shi, Yang Yu, Qing Da, Shi-Yong Chen, An-Xiang Zeng. AAAI 2019. [paper](http://www.lamda.nju.edu.cn/yuy/GetFile.aspx?File=papers/aaai2019-virtualtaobao.pdf)
 1. **A Model-Based Reinforcement Learning with Adversarial Training for Online Recommendation**. Xueying Bai, Jian Guan, Hongning Wang. NeurIPS 2019. [paper](http://papers.nips.cc/paper/9257-a-model-based-reinforcement-learning-with-adversarial-training-for-online-recommendation.pdf)
 1. **Text-Based Interactive Recommendation via Constraint-Augmented Reinforcement Learning**. Ruiyi Zhang, Tong Yu, Yilin Shen, Hongxia Jin, Changyou Chen, Lawrence Carin. NeurIPS 2019. [paper](http://people.ee.duke.edu/~lcarin/Ruiyi_NeurIPS2019.pdf)
-1. **Policy Gradients for Contextual Recommendations**. Feiyang Pan, Qingpeng Cai, Pingzhong Tang, Fuzhen Zhuang, Qing He. WWW 2019. [paper](https://arxiv.org/pdf/1802.04162.pdf)
+1. **Pseudo Dyna-Q: A Reinforcement Learning Framework for Interactive Recommendation**. Lixin Zou, Long Xia, Pan Du, Zhuo Zhang, Ting Bai, Weidong Liu, Jian-Yun Nie, Dawei Yin. WSDM 2020. [paper](https://tbbaby.github.io/pub/wsdm20.pdf)
+1. **End-to-End Deep Reinforcement Learning based Recommendation with Supervised Embedding**. Feng Liu, Huifeng Guo, Xutao Li, Ruiming Tang, Yunming Ye, Xiuqiang He. WSDM 2020. [paper](https://dl.acm.org/doi/abs/10.1145/3336191.3371858)
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 ### Preprint Papers
 1. **Reinforcement Learning based Recommender System using Biclustering Technique**. Sungwoon Choi, Heonseok Ha, Uiwon Hwang, Chanju Kim, Jung-Woo Ha, Sungroh Yoon. arxiv 2018. [paper](https://arxiv.org/pdf/1801.05532.pdf)