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2020 – today
- 2024
[j3]Dan Zhang
, Wenzheng Feng, Yuandong Wang, Zhongang Qi, Ying Shan, Jie Tang:
DropConn: Dropout Connection Based Random GNNs for Molecular Property Prediction. IEEE Trans. Knowl. Data Eng. 36(2): 518-529 (2024)- [c14]Tianyu Zhang, Yuxiang Ren, Wenzheng Feng, Weitao Du, Xuecang Zhang:
CGCL: Collaborative Graph Contrastive Learning Without Handcrafted Graph Data Augmentations. DASFAA (6) 2024: 418-428 - [i6]Guoxin Chen, Zhong Zhang, Xin Cong, Fangda Guo, Yesai Wu, Yankai Lin, Wenzheng Feng, Yasheng Wang:
Learning Evolving Tools for Large Language Models. CoRR abs/2410.06617 (2024) - 2023
- [j2]Jibing Gong, Yao Wan, Ye Liu, Xuewen Li, Yi Zhao, Cheng Wang, Yuting Lin, Xiaohan Fang, Wenzheng Feng, Jingyi Zhang, Jie Tang:
Reinforced MOOCs Concept Recommendation in Heterogeneous Information Networks. ACM Trans. Web 17(3): 22:1-22:27 (2023) - [c13]Yifan Zhu, Fangpeng Cong, Dan Zhang, Wenwen Gong, Qika Lin, Wenzheng Feng, Yuxiao Dong, Jie Tang:
WinGNN: Dynamic Graph Neural Networks with Random Gradient Aggregation Window. KDD 2023: 3650-3662 - [c12]Ming Zhou, Wenzheng Feng, Yifan Zhu, Dan Zhang, Yuxiao Dong, Jie Tang:
Semi-Supervised Social Bot Detection with Initial Residual Relation Attention Networks. ECML/PKDD (6) 2023: 207-224 - [c11]Dan Zhang, Yifan Zhu, Yuxiao Dong, Yuandong Wang, Wenzheng Feng, Evgeny Kharlamov, Jie Tang:
ApeGNN: Node-Wise Adaptive Aggregation in GNNs for Recommendation. WWW 2023: 759-769 - 2022
- [c10]Wenzheng Feng, Yuxiao Dong, Tinglin Huang, Ziqi Yin, Xu Cheng, Evgeny Kharlamov, Jie Tang:
GRAND+: Scalable Graph Random Neural Networks. WWW 2022: 3248-3258 - [i5]Wenzheng Feng, Yuxiao Dong, Tinglin Huang, Ziqi Yin, Xu Cheng, Evgeny Kharlamov, Jie Tang:
GRAND+: Scalable Graph Random Neural Networks. CoRR abs/2203.06389 (2022) - [i4]Jibing Gong, Yao Wan, Ye Liu, Xuewen Li, Yi Zhao, Cheng Wang, Qing Li, Wenzheng Feng, Jie Tang:
Reinforced MOOCs Concept Recommendation in Heterogeneous Information Networks. CoRR abs/2203.11011 (2022) - 2021
- [j1]Zhengyang Song, Jie Tang, Tracy Xiao Liu, Wenjiang Zheng, Lili Wu, Wenzheng Feng, Jing Zhang:
XiaoMu: an AI-driven assistant for MOOCs. Sci. China Inf. Sci. 64(6) (2021) - [c9]Jifan Yu, Yuquan Wang, Qingyang Zhong, Gan Luo, Yiming Mao, Kai Sun, Wenzheng Feng, Wei Xu, Shulin Cao, Kaisheng Zeng, Zijun Yao, Lei Hou, Yankai Lin, Peng Li, Jie Zhou, Bin Xu, Juanzi Li, Jie Tang, Maosong Sun:
MOOCCubeX: A Large Knowledge-centered Repository for Adaptive Learning in MOOCs. CIKM 2021: 4643-4652 - [c8]Tinglin Huang, Yuxiao Dong, Ming Ding, Zhen Yang, Wenzheng Feng, Xinyu Wang, Jie Tang:
MixGCF: An Improved Training Method for Graph Neural Network-based Recommender Systems. KDD 2021: 665-674 - [c7]Qingsong Lv, Ming Ding, Qiang Liu, Yuxiang Chen, Wenzheng Feng, Siming He, Chang Zhou, Jianguo Jiang, Yuxiao Dong, Jie Tang:
Are we really making much progress?: Revisiting, benchmarking and refining heterogeneous graph neural networks. KDD 2021: 1150-1160 - [i3]Qingsong Lv, Ming Ding, Qiang Liu, Yuxiang Chen, Wenzheng Feng, Siming He, Chang Zhou, Jianguo Jiang, Yuxiao Dong, Jie Tang:
Are we really making much progress? Revisiting, benchmarking, and refining heterogeneous graph neural networks. CoRR abs/2112.14936 (2021) - 2020
- [c6]Jifan Yu, Gan Luo, Tong Xiao, Qingyang Zhong, Yuquan Wang, Wenzheng Feng, Junyi Luo, Chenyu Wang, Lei Hou, Juanzi Li, Zhiyuan Liu, Jie Tang:
MOOCCube: A Large-scale Data Repository for NLP Applications in MOOCs. ACL 2020: 3135-3142 - [c5]Wenzheng Feng, Jie Zhang, Yuxiao Dong, Yu Han, Huanbo Luan, Qian Xu, Qiang Yang, Evgeny Kharlamov, Jie Tang:
Graph Random Neural Networks for Semi-Supervised Learning on Graphs. NeurIPS 2020 - [c4]Jibing Gong, Shen Wang, Jinlong Wang, Wenzheng Feng, Hao Peng, Jie Tang, Philip S. Yu:
Attentional Graph Convolutional Networks for Knowledge Concept Recommendation in MOOCs in a Heterogeneous View. SIGIR 2020: 79-88 - [i2]Wenzheng Feng, Jie Zhang, Yuxiao Dong, Yu Han, Huanbo Luan, Qian Xu, Qiang Yang, Jie Tang:
Graph Random Neural Network. CoRR abs/2005.11079 (2020) - [i1]Shen Wang, Jibing Gong, Jinlong Wang, Wenzheng Feng, Hao Peng, Jie Tang, Philip S. Yu:
Attentional Graph Convolutional Networks for Knowledge Concept Recommendation in MOOCs in a Heterogeneous View. CoRR abs/2006.13257 (2020)
2010 – 2019
- 2019
- [c3]Wenzheng Feng, Jie Tang, Tracy Xiao Liu:
Understanding Dropouts in MOOCs. AAAI 2019: 517-524 - 2018
- [c2]Xiaochen Wang, Wenzheng Feng, Jie Tang, Qingyang Zhong:
Course Concept Extraction in MOOC via Explicit/Implicit Representation. DSC 2018: 339-345 - 2017
- [c1]Wenzheng Feng, Yu Wu, Wei Wu, Zhoujun Li, Ming Zhou:
Beihang-MSRA at SemEval-2017 Task 3: A Ranking System with Neural Matching Features for Community Question Answering. SemEval@ACL 2017: 280-286
Coauthor Index
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