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2020 – today
- 2022
[c18]Shijie Geng, Zuohui Fu, Yingqiang Ge, Lei Li, Gerard de Melo, Yongfeng Zhang:
Improving Personalized Explanation Generation through Visualization. ACL (1) 2022: 244-255- [c17]Yingqiang Ge, Xiaoting Zhao, Lucia Yu, Saurabh Paul, Diane Hu, Chu-Cheng Hsieh, Yongfeng Zhang:
Toward Pareto Efficient Fairness-Utility Trade-off in Recommendation through Reinforcement Learning. WSDM 2022: 316-324 - [c16]Shijie Geng, Zuohui Fu, Juntao Tan, Yingqiang Ge, Gerard de Melo, Yongfeng Zhang:
Path Language Modeling over Knowledge Graphsfor Explainable Recommendation. WWW 2022: 946-955 - [c15]Juntao Tan, Shijie Geng, Zuohui Fu, Yingqiang Ge, Shuyuan Xu, Yunqi Li, Yongfeng Zhang:
Learning and Evaluating Graph Neural Network Explanations based on Counterfactual and Factual Reasoning. WWW 2022: 1018-1027 - [i20]Yingqiang Ge, Xiaoting Zhao, Lucia Yu, Saurabh Paul, Diane Hu, Chu-Cheng Hsieh, Yongfeng Zhang:
Toward Pareto Efficient Fairness-Utility Trade-off inRecommendation through Reinforcement Learning. CoRR abs/2201.00140 (2022) - [i19]Juntao Tan, Shijie Geng, Zuohui Fu, Yingqiang Ge, Shuyuan Xu, Yunqi Li, Yongfeng Zhang:
Learning and Evaluating Graph Neural Network Explanations based on Counterfactual and Factual Reasoning. CoRR abs/2202.08816 (2022) - [i18]Shijie Geng, Shuchang Liu, Zuohui Fu, Yingqiang Ge, Yongfeng Zhang:
Recommendation as Language Processing (RLP): A Unified Pretrain, Personalized Prompt & Predict Paradigm (P5). CoRR abs/2203.13366 (2022) - [i17]Yingqiang Ge, Juntao Tan, Yan Zhu, Yinglong Xia, Jiebo Luo, Shuchang Liu, Zuohui Fu, Shijie Geng, Zelong Li, Yongfeng Zhang:
Explainable Fairness in Recommendation. CoRR abs/2204.11159 (2022) - [i16]Zelong Li, Jianchao Ji, Yingqiang Ge, Yongfeng Zhang:
AutoLossGen: Automatic Loss Function Generation for Recommender Systems. CoRR abs/2204.13160 (2022) - [i15]Yunqi Li, Hanxiong Chen, Shuyuan Xu, Yingqiang Ge, Juntao Tan, Shuchang Liu, Yongfeng Zhang:
Fairness in Recommendation: A Survey. CoRR abs/2205.13619 (2022) - 2021
- [c14]Juntao Tan, Shuyuan Xu, Yingqiang Ge, Yunqi Li, Xu Chen, Yongfeng Zhang:
Counterfactual Explainable Recommendation. CIKM 2021: 1784-1793 - [c13]Yunqi Li, Yingqiang Ge, Yongfeng Zhang:
CIKM 2021 Tutorial on Fairness of Machine Learning in Recommender Systems. CIKM 2021: 4857-4860 - [c12]Yunqi Li, Hanxiong Chen, Shuyuan Xu, Yingqiang Ge, Yongfeng Zhang:
Towards Personalized Fairness based on Causal Notion. SIGIR 2021: 1054-1063 - [c11]Yunqi Li, Yingqiang Ge, Yongfeng Zhang:
Tutorial on Fairness of Machine Learning in Recommender Systems. SIGIR 2021: 2654-2657 - [c10]Yingqiang Ge, Shuchang Liu, Ruoyuan Gao, Yikun Xian, Yunqi Li, Xiangyu Zhao, Changhua Pei, Fei Sun, Junfeng Ge, Wenwu Ou, Yongfeng Zhang:
Towards Long-term Fairness in Recommendation. WSDM 2021: 445-453 - [c9]Shuchang Liu, Fei Sun, Yingqiang Ge, Changhua Pei, Yongfeng Zhang:
Variation Control and Evaluation for Generative Slate Recommendations. WWW 2021: 436-448 - [c8]Yunqi Li, Hanxiong Chen, Zuohui Fu, Yingqiang Ge, Yongfeng Zhang:
User-oriented Fairness in Recommendation. WWW 2021: 624-632 - [c7]Zelong Li, Jianchao Ji, Zuohui Fu, Yingqiang Ge, Shuyuan Xu, Chong Chen, Yongfeng Zhang:
Efficient Non-Sampling Knowledge Graph Embedding. WWW 2021: 1727-1736 - [i14]Yingqiang Ge, Shuchang Liu, Ruoyuan Gao, Yikun Xian, Yunqi Li, Xiangyu Zhao, Changhua Pei, Fei Sun, Junfeng Ge, Wenwu Ou, Yongfeng Zhang:
Towards Long-term Fairness in Recommendation. CoRR abs/2101.03584 (2021) - [i13]Shuyuan Xu, Yingqiang Ge, Yunqi Li, Zuohui Fu, Xu Chen, Yongfeng Zhang:
Causal Collaborative Filtering. CoRR abs/2102.01868 (2021) - [i12]Shuchang Liu, Fei Sun, Yingqiang Ge, Changhua Pei, Yongfeng Zhang:
Variation Control and Evaluation for Generative SlateRecommendations. CoRR abs/2102.13302 (2021) - [i11]Yunqi Li, Hanxiong Chen, Zuohui Fu, Yingqiang Ge, Yongfeng Zhang:
User-oriented Fairness in Recommendation. CoRR abs/2104.10671 (2021) - [i10]Zelong Li, Jianchao Ji, Zuohui Fu, Yingqiang Ge, Shuyuan Xu, Chong Chen, Yongfeng Zhang:
Efficient Non-Sampling Knowledge Graph Embedding. CoRR abs/2104.10796 (2021) - [i9]Yunqi Li, Hanxiong Chen, Shuyuan Xu, Yingqiang Ge, Yongfeng Zhang:
Towards Personalized Fairness based on Causal Notion. CoRR abs/2105.09829 (2021) - [i8]Ruoyuan Gao, Yingqiang Ge, Chirag Shah:
FAIR: Fairness-Aware Information Retrieval Evaluation. CoRR abs/2106.08527 (2021) - [i7]Juntao Tan, Shuyuan Xu, Yingqiang Ge, Yunqi Li, Xu Chen, Yongfeng Zhang:
Counterfactual Explainable Recommendation. CoRR abs/2108.10539 (2021) - [i6]Yingqiang Ge, Shuchang Liu, Zelong Li, Shuyuan Xu, Shijie Geng, Yunqi Li, Juntao Tan, Fei Sun, Yongfeng Zhang:
Counterfactual Evaluation for Explainable AI. CoRR abs/2109.01962 (2021) - 2020
- [c6]Zuohui Fu, Yikun Xian, Shijie Geng, Yingqiang Ge, Yuting Wang, Xin Dong, Guang Wang, Gerard de Melo:
ABSent: Cross-Lingual Sentence Representation Mapping with Bidirectional GANs. AAAI 2020: 7756-7763 - [c5]Yikun Xian, Zuohui Fu, Handong Zhao, Yingqiang Ge, Xu Chen, Qiaoying Huang, Shijie Geng, Zhou Qin, Gerard de Melo, S. Muthukrishnan, Yongfeng Zhang:
CAFE: Coarse-to-Fine Neural Symbolic Reasoning for Explainable Recommendation. CIKM 2020: 1645-1654 - [c4]Zuohui Fu, Yikun Xian, Ruoyuan Gao, Jieyu Zhao, Qiaoying Huang, Yingqiang Ge, Shuyuan Xu, Shijie Geng, Chirag Shah, Yongfeng Zhang, Gerard de Melo:
Fairness-Aware Explainable Recommendation over Knowledge Graphs. SIGIR 2020: 69-78 - [c3]Yingqiang Ge, Shuyuan Xu, Shuchang Liu, Zuohui Fu, Fei Sun, Yongfeng Zhang:
Learning Personalized Risk Preferences for Recommendation. SIGIR 2020: 409-418 - [c2]Yingqiang Ge, Shuya Zhao, Honglu Zhou, Changhua Pei, Fei Sun, Wenwu Ou, Yongfeng Zhang:
Understanding Echo Chambers in E-commerce Recommender Systems. SIGIR 2020: 2261-2270 - [i5]Zuohui Fu, Yikun Xian, Shijie Geng, Yingqiang Ge, Yuting Wang, Xin Dong, Guang Wang, Gerard de Melo:
ABSent: Cross-Lingual Sentence Representation Mapping with Bidirectional GANs. CoRR abs/2001.11121 (2020) - [i4]Zuohui Fu, Yikun Xian, Ruoyuan Gao, Jieyu Zhao, Qiaoying Huang, Yingqiang Ge, Shuyuan Xu, Shijie Geng, Chirag Shah, Yongfeng Zhang, Gerard de Melo:
Fairness-Aware Explainable Recommendation over Knowledge Graphs. CoRR abs/2006.02046 (2020) - [i3]Yingqiang Ge, Shuya Zhao, Honglu Zhou, Changhua Pei, Fei Sun, Wenwu Ou, Yongfeng Zhang:
Understanding Echo Chambers in E-commerce Recommender Systems. CoRR abs/2007.02474 (2020) - [i2]Yingqiang Ge, Shuyuan Xu, Shuchang Liu, Zuohui Fu, Fei Sun, Yongfeng Zhang:
Learning Personalized Risk Preferences for Recommendation. CoRR abs/2007.02478 (2020) - [i1]Yikun Xian, Zuohui Fu, Handong Zhao, Yingqiang Ge, Xu Chen, Qiaoying Huang, Shijie Geng, Zhou Qin, Gerard de Melo, S. Muthukrishnan, Yongfeng Zhang:
CAFE: Coarse-to-Fine Neural Symbolic Reasoning for Explainable Recommendation. CoRR abs/2010.15620 (2020)
2010 – 2019
- 2019
- [j1]Guang Wang, Wenzhong Li, Jun Zhang, Yingqiang Ge, Zuohui Fu, Fan Zhang, Yang Wang, Desheng Zhang
:
sharedCharging: Data-Driven Shared Charging for Large-Scale Heterogeneous Electric Vehicle Fleets. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 3(3): 108:1-108:25 (2019) - [c1]Yingqiang Ge, Shuyuan Xu, Shuchang Liu, Shijie Geng, Zuohui Fu, Yongfeng Zhang:
Maximizing Marginal Utility per Dollar for Economic Recommendation. WWW 2019: 2757-2763
Coauthor Index
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