| Anomaly detection in dynamic networks: a survey S Ranshous, S Shen, D Koutra, S Harenberg, C Faloutsos, NF Samatova Wiley Interdisciplinary Reviews: Computational Statistics 7 (3), 223-247, 2015 | 460 | 2015 |
| Reinforcement learning: the sooner the better, or the later the better? S Shen, M Chi Proceedings of the 2016 conference on user modeling adaptation and …, 2016 | 62 | 2016 |
| Clustering Student Sequential Trajectories Using Dynamic Time Warping. S Shen, M Chi International Educational Data Mining Society, 2017 | 33 | 2017 |
| Aim Low: Correlation-Based Feature Selection for Model-Based Reinforcement Learning. S Shen, M Chi International Educational Data Mining Society, 2016 | 33 | 2016 |
| Incorporating student response time and tutor instructional interventions into student modeling C Lin, S Shen, M Chi Proceedings of the 2016 Conference on user modeling adaptation and …, 2016 | 29 | 2016 |
| Improving learning & reducing time: A constrained action-based reinforcement learning approach S Shen, MS Ausin, B Mostafavi, M Chi Proceedings of the 26th conference on user modeling, adaptation and …, 2018 | 26 | 2018 |
| Exploring induced pedagogical strategies through a Markov decision process framework: Lessons learned S Shen, B Mostafavi Journal of educational data mining 10 (3), 2018 | 23 | 2018 |
| Empirically evaluating the effectiveness of pomdp vs. mdp towards the pedagogical strategies induction S Shen, B Mostafavi, C Lynch, T Barnes, M Chi Artificial Intelligence in Education: 19th International Conference, AIED …, 2018 | 12 | 2018 |
| Importance Sampling to Identify Empirically Valid Policies and their Critical Decisions. S Ju, S Shen, H Azizsoltani, T Barnes, M Chi EDM (Workshops), 69-78, 2019 | 8 | 2019 |
| DynLLM: When Large Language Models Meet Dynamic Graph Recommendation Z Zhao, F Lin, X Zhu, Z Zheng, T Xu, S Shen, X Li, Z Yin, E Chen arXiv preprint arXiv:2405.07580, 2024 | 5 | 2024 |
| When box meets graph neural network in tag-aware recommendation F Lin, Z Zhao, X Zhu, D Zhang, S Shen, X Li, T Xu, S Zhang, E Chen Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and …, 2024 | 4 | 2024 |
| Competitive intelligence changes in big data era based on literature analysis M Li, R SUN, H Fu, S Shen 2016 3rd International Conference on Economics and Management (ICEM 2016), 2016 | 4 | 2016 |
| Jointly Multi-Similarity Loss for Deep Metric Learning L Zhang, S Shen, L Li, H Wang, X Li, J Lang 2021 IEEE International Conference on Data Mining (ICDM), 1469-1474, 2021 | 2 | 2021 |
| Modeling the process of online q&a discussions using a dialogue state model S Shen, J Kim Artificial Intelligence in Education: 16th International Conference, AIED …, 2013 | 2 | 2013 |
| APPLICATIONS C S Shen, M Shimmei, M Chi, N Matsuda Design Recommendations for Intelligent Tutoring Systems: Volume 7-Self …, 2019 | 1 | 2019 |
| Empirically Evaluating the Application of POMDP vs. MDP Towards the Induction of Pedagogical Strategies. S Shen, B Mostafavi, C Lynch, T Barnes, M Chi In Proceedings of the 19th International Conference on Artificial …, 2018 | 1 | 2018 |
| –APPLICATIONS OF REINFORCEMENT LEARNING TO SELF IMPROVING EDUCATIONAL SYSTEMS S Shen, M Shimmei, M Chi, N Matsuda Design Recommendations for Intelligent Tutoring Systems 7, 77-96, 2019 | | 2019 |
| Reciprocity in Student Online Discussions S Shen, J Kim, J Yoo International Society of the Learning Sciences, 2013 | | 2013 |
| An Analysis of Feature Selection and Reward Function for Model-Based Reinforcement Learning S Shen, C Lin, B Mostafavi, T Barnes, M Chi Intelligent Tutoring Systems, 504, 0 | | |