| A fast clustering-based feature subset selection algorithm for high-dimensional data Q Song, J Ni, G Wang IEEE transactions on knowledge and data engineering 25 (1), 1-14, 2011 | 829 | 2011 |
| Select, answer and explain: Interpretable multi-hop reading comprehension over multiple documents M Tu, K Huang, G Wang, J Huang, X He, B Zhou Proceedings of the AAAI Conference on Artificial Intelligence 34 (05), 9073-9080, 2020 | 192 | 2020 |
| Multi-hop Reading Comprehension across Multiple Documents by Reasoning over Heterogeneous Graphs M Tu, G Wang, J Huang, Y Tang, X He, B Zhou Association for Computational Linguistics, 2019 | 183 | 2019 |
| Multi-hop Attention Graph Neural Network G Wang, Z Ying, J Huang, J Leskovec IJCAI 2021, 2020 | 170* | 2020 |
| A feature subset selection algorithm automatic recommendation method G Wang, Q Song, H Sun, X Zhang, B Xu, Y Zhou Journal of Artificial Intelligence Research 47, 1-34, 2013 | 107 | 2013 |
| Automatic recommendation of classification algorithms based on data set characteristics Q Song, G Wang, C Wang Pattern recognition 45 (7), 2672-2689, 2012 | 104 | 2012 |
| Orthogonal Relation Transforms with Graph Context Modeling for Knowledge Graph Embedding Y Tang, J Huang, G Wang, X He, B Zhou Association for Computational Linguistics, 2020 | 102 | 2020 |
| Automatic clustering via outward statistical testing on density metrics G Wang, Q Song IEEE Transactions on Knowledge and Data Engineering 28 (8), 1971-1985, 2016 | 98 | 2016 |
| Improving Graph Attention Networks with Large Margin-based Constraints G Wang, R Ying, J Huang, J Leskovec NerIPS 2019 (Graph Representation Learning-workshop), 2019 | 96 | 2019 |
| Improving neural language generation with spectrum control L Wang, J Huang, K Huang, Z Hu, G Wang, Q Gu International Conference on Learning Representations, 2019 | 88 | 2019 |
| Selecting feature subset for high dimensional data via the propositional FOIL rules G Wang, Q Song, B Xu, Y Zhou Pattern Recognition 46 (1), 199-214, 2013 | 69 | 2013 |
| Selective attention based graph convolutional networks for aspect-level sentiment classification X Hou, J Huang, G Wang, X He, B Zhou Proceedings of the Fifteenth Workshop on Graph-Based Methods for Natural …, 2021 | 66 | 2021 |
| Graph Ensemble Learning over Multiple Dependency Trees for Aspect-level Sentiment Classification X Hou, P Qi, G Wang, R Ying, J Huang, X He, B Zhou NAACL, 2021 | 63 | 2021 |
| A new unsupervised feature selection algorithm using similarity‐based feature clustering X Zhu, Y Wang, Y Li, Y Tan, G Wang, Q Song Computational Intelligence 35 (1), 2-22, 2019 | 60 | 2019 |
| Dynamic ensemble learning for multi-label classification X Zhu, J Li, J Ren, J Wang, G Wang Information Sciences 623, 94-111, 2023 | 50 | 2023 |
| A dissimilarity-based imbalance data classification algorithm X Zhang, Q Song, G Wang, K Zhang, L He, X Jia Applied Intelligence 42, 544-565, 2015 | 47 | 2015 |
| Entity and evidence guided document-level relation extraction K Huang, P Qi, G Wang, T Ma, J Huang Proceedings of the 6th Workshop on Representation Learning for NLP (RepL4NLP …, 2021 | 43* | 2021 |
| CenLP: A centrality-based label propagation algorithm for community detection in networks H Sun, J Liu, J Huang, G Wang, Z Yang, Q Song, X Jia Physica A: Statistical Mechanics and its Applications 436, 767-780, 2015 | 39 | 2015 |
| Improving Time Sensitivity for Question Answering over Temporal Knowledge Graphs C Shang, G Wang, P Qi, J Huang arXiv preprint arXiv:2203.00255, 2022 | 38 | 2022 |
| Inductive Learning on Commonsense Knowledge Graph Completion B Wang, G Wang, J Huang, J You, J Leskovec, CCJ Kuo 2021 International Joint Conference on Neural Networks (IJCNN), 1-8, 2021 | 38 | 2021 |
Jing HuangAmazon/Stanford SAIL/JD AI Research/Apple Siri/IBM ResearchVerified email at amazon.com
