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Knowledge Graph-Based Reinforcement Federated Learning for Chinese Question and Answering Journal article
Xu,Liang, Chen,Tao, Hou,Zhaoxiang, Zhang,Weishan, Hon,Chitin, Wang,Xiao, Wang,Di, Chen,Long, Zhu,Wenyin, Tian,Yunlong, Ning,Huansheng, Wang,Fei Yue. Knowledge Graph-Based Reinforcement Federated Learning for Chinese Question and Answering[J]. IEEE Transactions on Computational Social Systems, 2024, 11(1), 1035-1045.
Authors:  Xu,Liang;  Chen,Tao;  Hou,Zhaoxiang;  Zhang,Weishan;  Hon,Chitin; et al.
Favorite | TC[WOS]:3 TC[Scopus]:4  IF:4.5/4.6 | Submit date：2023/08/03
Knowledge Graph  Multitask Semantic Parsing [Msp-bidirectional And Auto-regressive Transformers (Bart)]  Prompt Learning  Question And Answering (q&a)  Reinforcement Federated Learning (Rfl)  
Integrating metabolomic data with machine learning approach for discovery of Q-markers from Jinqi Jiangtang preparation against type 2 diabetes Journal article
Yang, Lele, Xue, Yan, Wei, Jinchao, Dai, Qi, Li, Peng. Integrating metabolomic data with machine learning approach for discovery of Q-markers from Jinqi Jiangtang preparation against type 2 diabetes[J]. Chinese Medicine, 2021, 16(1), 30.
Authors:  Yang, Lele;  Xue, Yan;  Wei, Jinchao;  Dai, Qi;  Li, Peng
Favorite | TC[WOS]:14 TC[Scopus]:15  IF:5.3/5.5 | Submit date：2021/12/09
Backpropagation Artificial Neural Network  Jinqi Jiangtang  Machine Learning  Mass Spectrometry  Metabolomics  Q-markers  
Energy-Efficient UAV-Enabled Data Collection via Wireless Charging: A Reinforcement Learning Approach Journal article
Fu Shu, Tang Yujie, Wu Yuan, Zhang Ning, Gu Huaxi, Chen Chen, Liu Min. Energy-Efficient UAV-Enabled Data Collection via Wireless Charging: A Reinforcement Learning Approach[J]. IEEE Internet of Things Journal, 2021, 8(12), 10209-10219.
Authors:  Fu Shu;  Tang Yujie;  Wu Yuan;  Zhang Ning;  Gu Huaxi; et al.
Favorite | TC[WOS]:67 TC[Scopus]:86  IF:8.2/9.0 | Submit date：2021/09/10
Data Collection  Design Of Reward Function  Energy Efficiency  Q-learning  Reinforcement Learning  Unmanned Aerial Vehicle (Uav)  
SMig-RL: An evolutionary migration framework for cloud services based on deep reinforcement learning Journal article
Ren,Hongshuai, Wang,Yang, Xu,Chengzhong, Chen,Xi. SMig-RL: An evolutionary migration framework for cloud services based on deep reinforcement learning[J]. ACM Transactions on Internet Technology, 2020, 20(4).
Authors:  Ren,Hongshuai;  Wang,Yang;  Xu,Chengzhong;  Chen,Xi
Favorite | TC[WOS]:7 TC[Scopus]:7  IF:3.9/3.6 | Submit date：2021/03/09
Cloud Computing  Deep Reinforcement Learning  Dynamic Service Migration  Mobile Access  Q-learning  Rnn  
Towards cost-effective service migration in mobile edge: A Q-learning approach Journal article
Wang,Yang, Cao,Shan, Ren,Hongshuai, Li,Jianjun, Ye,Kejiang, Xu,Chengzhong, Chen,Xi. Towards cost-effective service migration in mobile edge: A Q-learning approach[J]. Journal of Parallel and Distributed Computing, 2020, 146, 175-188.
Authors:  Wang,Yang;  Cao,Shan;  Ren,Hongshuai;  Li,Jianjun;  Ye,Kejiang; et al.
Favorite | TC[WOS]:6 TC[Scopus]:12  IF:3.4/3.4 | Submit date：2021/03/09
Mobile Edge Computing  Dynamic Service Migration  Reinforcement Learning  Q-learning  Software-defined Networking  
Towards Personalized Learning Through Class Contextual Factors-Based Exercise Recommendation Conference paper
Huo, Yujia, Xiao, Jiang, Ni, Lionel M.. Towards Personalized Learning Through Class Contextual Factors-Based Exercise Recommendation[C], 2019, 85-92.
Authors:  Huo, Yujia;  Xiao, Jiang;  Ni, Lionel M.
Favorite | TC[WOS]:9 TC[Scopus]:12 | Submit date：2022/04/15
Attribute-based Recommendation  Learning Remediation  Performance Prediction  Personalized Learning  Q-matrix  Recommender Systems  
Online adjusting subway timetable by q-learning to save energy consumption in uncertain passenger demand Conference paper
Yin J., Chen D., Zhao W., Chen L.. Online adjusting subway timetable by q-learning to save energy consumption in uncertain passenger demand[C], 2014, 2743-2748.
Authors:  Yin J.;  Chen D.;  Zhao W.;  Chen L.
Favorite | TC[WOS]:5 TC[Scopus]:10 | Submit date：2019/02/13
Energy-efficient  Intelligent Train Operation  Q-learning  Subway System  Timetable