Stop the war!Остановите войну!
for scientists:
default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDSuhang Wang
Person information
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2023
[j21]Enyan Dai
, Suhang Wang:
Learning Fair Graph Neural Networks With Limited and Private Sensitive Attribute Information. IEEE Trans. Knowl. Data Eng. 35(7): 7103-7117 (2023)- [c97]Wenqi Fan, Han Xu, Wei Jin, Xiaorui Liu, Xianfeng Tang, Suhang Wang, Qing Li, Jiliang Tang, Jianping Wang, Charu C. Aggarwal:
Jointly Attacking Graph Neural Network and its Explanations. ICDE 2023: 654-667 - [c96]Enyan Dai, Limeng Cui, Zhengyang Wang, Xianfeng Tang, Yinghan Wang, Monica Xiao Cheng, Bing Yin, Suhang Wang:
A Unified Framework of Graph Information Bottleneck for Robustness and Membership Privacy. KDD 2023: 368-379 - [c95]Teng Xiao, Zhengyu Chen, Suhang Wang:
Reconsidering Learning Objectives in Unbiased Recommendation: A Distribution Shift Perspective. KDD 2023: 2764-2775 - [c94]Tianxiang Zhao, Wenchao Yu, Suhang Wang, Lu Wang, Xiang Zhang, Yuncong Chen, Yanchi Liu, Wei Cheng, Haifeng Chen:
Skill Disentanglement for Imitation Learning from Suboptimal Demonstrations. KDD 2023: 3513-3524 - [c93]Yu Wang, Zhengyang Wang, Hengrui Zhang, Qingyu Yin, Xianfeng Tang, Yinghan Wang, Danqing Zhang, Limeng Cui, Monica Cheng, Bing Yin, Suhang Wang, Philip S. Yu:
Exploiting Intent Evolution in E-commercial Query Recommendation. KDD 2023: 5162-5173 - [c92]Huaisheng Zhu, Xianfeng Tang, Tianxiang Zhao, Suhang Wang:
You Need to Look Globally: Discovering Representative Topology Structures to Enhance Graph Neural Network. PAKDD (2) 2023: 40-52 - [c91]Wanda Li, Wenhao Zheng, Xuanji Xiao, Suhang Wang:
STAN: Stage-Adaptive Network for Multi-Task Recommendation by Learning User Lifecycle-Based Representation. RecSys 2023: 602-612 - [c90]Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang:
Towards Faithful and Consistent Explanations for Graph Neural Networks. WSDM 2023: 634-642 - [c89]Enyan Dai, Minhua Lin, Xiang Zhang, Suhang Wang:
Unnoticeable Backdoor Attacks on Graph Neural Networks. WWW 2023: 2263-2273 - [i64]Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang:
Faithful and Consistent Graph Neural Network Explanations with Rationale Alignment. CoRR abs/2301.02791 (2023) - [i63]Enyan Dai, Minhua Lin, Xiang Zhang, Suhang Wang:
Unnoticeable Backdoor Attacks on Graph Neural Networks. CoRR abs/2303.01263 (2023) - [i62]Zhimeng Guo, Teng Xiao, Charu Aggarwal, Hui Liu, Suhang Wang:
Counterfactual Learning on Graphs: A Survey. CoRR abs/2304.01391 (2023) - [i61]Huaisheng Zhu, Dongsheng Luo, Xianfeng Tang, Junjie Xu, Hui Liu, Suhang Wang:
Self-Explainable Graph Neural Networks for Link Prediction. CoRR abs/2305.12578 (2023) - [i60]Tianxiang Zhao, Wenchao Yu, Suhang Wang, Lu Wang, Xiang Zhang, Yuncong Chen, Yanchi Liu, Wei Cheng, Haifeng Chen:
Skill Disentanglement for Imitation Learning from Suboptimal Demonstrations. CoRR abs/2306.07919 (2023) - [i59]Enyan Dai, Limeng Cui, Zhengyang Wang, Xianfeng Tang, Yinghan Wang, Monica Xiao Cheng, Bing Yin, Suhang Wang:
A Unified Framework of Graph Information Bottleneck for Robustness and Membership Privacy. CoRR abs/2306.08604 (2023) - [i58]Huaisheng Zhu, Guoji Fu, Zhimeng Guo, Zhiwei Zhang, Teng Xiao, Suhang Wang:
Fairness-aware Message Passing for Graph Neural Networks. CoRR abs/2306.11132 (2023) - [i57]Wanda Li, Wenhao Zheng, Xuanji Xiao, Suhang Wang:
STAN: Stage-Adaptive Network for Multi-Task Recommendation by Learning User Lifecycle-Based Representation. CoRR abs/2306.12232 (2023) - [i56]Yang Li, Kangbo Liu, Ranjan Satapathy, Suhang Wang, Erik Cambria:
Recent Developments in Recommender Systems: A Survey. CoRR abs/2306.12680 (2023) - [i55]Zhimeng Guo, Jialiang Li, Teng Xiao, Yao Ma, Suhang Wang:
Improving Fairness of Graph Neural Networks: A Graph Counterfactual Perspective. CoRR abs/2307.04937 (2023) - [i54]Wei Jin, Haitao Mao, Zheng Li, Haoming Jiang, Chen Luo, Hongzhi Wen, Haoyu Han, Hanqing Lu, Zhengyang Wang, Ruirui Li, Zhen Li, Monica Xiao Cheng, Rahul Goutam, Haiyang Zhang, Karthik Subbian, Suhang Wang, Yizhou Sun, Jiliang Tang, Bing Yin, Xianfeng Tang:
Amazon-M2: A Multilingual Multi-locale Shopping Session Dataset for Recommendation and Text Generation. CoRR abs/2307.09688 (2023) - 2022
- [j20]Wen Zhang, B. Blair Braden, Gustavo Miranda, Kai Shu, Suhang Wang, Huan Liu, Yalin Wang:
Integrating Multimodal and Longitudinal Neuroimaging Data with Multi-Source Network Representation Learning. Neuroinformatics 20(2): 301-316 (2022) - [c88]Teng Xiao, Suhang Wang:
Towards Off-Policy Learning for Ranking Policies with Logged Feedback. AAAI 2022: 8700-8707 - [c87]Teng Xiao, Zhengyu Chen, Suhang Wang:
Representation Matters When Learning From Biased Feedback in Recommendation. CIKM 2022: 2220-2229 - [c86]Junjie Xu, Enyan Dai, Xiang Zhang, Suhang Wang:
HP-GMN: Graph Memory Networks for Heterophilous Graphs. ICDM 2022: 1263-1268 - [c85]Enyan Dai, Shijie Zhou, Zhimeng Guo, Suhang Wang:
Label-Wise Graph Convolutional Network for Heterophilic Graphs. LoG 2022: 26 - [c84]Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang:
TopoImb: Toward Topology-Level Imbalance in Learning From Graphs. LoG 2022: 37 - [c83]Teng Xiao, Zhengyu Chen, Zhimeng Guo, Zeyang Zhuang, Suhang Wang:
Decoupled Self-supervised Learning for Graphs. NeurIPS 2022 - [c82]Enyan Dai, Wei Jin, Hui Liu, Suhang Wang:
Towards Robust Graph Neural Networks for Noisy Graphs with Sparse Labels. WSDM 2022: 181-191 - [c81]Xianfeng Tang, Yozen Liu, Xinran He, Suhang Wang, Neil Shah:
Friend Story Ranking with Edge-Contextual Local Graph Convolutions. WSDM 2022: 1007-1015 - [c80]Teng Xiao, Suhang Wang:
Towards Unbiased and Robust Causal Ranking for Recommender Systems. WSDM 2022: 1158-1167 - [c79]Tianxiang Zhao, Enyan Dai, Kai Shu, Suhang Wang:
Towards Fair Classifiers Without Sensitive Attributes: Exploring Biases in Related Features. WSDM 2022: 1433-1442 - [c78]Tianxiang Zhao, Xiang Zhang, Suhang Wang:
Exploring Edge Disentanglement for Node Classification. WWW 2022: 1028-1036 - [i53]Enyan Dai, Wei Jin, Hui Liu, Suhang Wang:
Towards Robust Graph Neural Networks for Noisy Graphs with Sparse Labels. CoRR abs/2201.00232 (2022) - [i52]Tianxiang Zhao, Xiang Zhang, Suhang Wang:
Exploring Edge Disentanglement for Node Classification. CoRR abs/2202.11245 (2022) - [i51]Huaisheng Zhu, Suhang Wang:
Learning Fair Models without Sensitive Attributes: A Generative Approach. CoRR abs/2203.16413 (2022) - [i50]Enyan Dai, Tianxiang Zhao, Huaisheng Zhu, Junjie Xu, Zhimeng Guo, Hui Liu, Jiliang Tang, Suhang Wang:
A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainability. CoRR abs/2204.08570 (2022) - [i49]Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang:
On Consistency in Graph Neural Network Interpretation. CoRR abs/2205.13733 (2022) - [i48]Teng Xiao, Zhengyu Chen, Zhimeng Guo, Zeyang Zhuang, Suhang Wang:
Decoupled Self-supervised Learning for Non-Homophilous Graphs. CoRR abs/2206.03601 (2022) - [i47]Teng Xiao, Zhengyu Chen, Suhang Wang:
Towards Bridging Algorithm and Theory for Unbiased Recommendation. CoRR abs/2206.03851 (2022) - [i46]Tianxiang Zhao, Xiang Zhang, Suhang Wang:
Synthetic Over-sampling for Imbalanced Node Classification with Graph Neural Networks. CoRR abs/2206.05335 (2022) - [i45]Shijie Zhou, Zhimeng Guo, Charu C. Aggarwal, Xiang Zhang, Suhang Wang:
Link Prediction on Heterophilic Graphs via Disentangled Representation Learning. CoRR abs/2208.01820 (2022) - [i44]Enyan Dai, Suhang Wang:
Towards Prototype-Based Self-Explainable Graph Neural Network. CoRR abs/2210.01974 (2022) - [i43]Junjie Xu, Enyan Dai, Xiang Zhang, Suhang Wang:
HP-GMN: Graph Memory Networks for Heterophilous Graphs. CoRR abs/2210.08195 (2022) - [i42]Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang:
TopoImb: Toward Topology-level Imbalance in Learning from Graphs. CoRR abs/2212.08689 (2022) - 2021
- [j19]Xuying Meng, Suhang Wang, Zhimin Liang, Di Yao, Jihua Zhou, Yujun Zhang:
Semi-supervised anomaly detection in dynamic communication networks. Inf. Sci. 571: 527-542 (2021) - [j18]Yang Li, Wei Zhao, Erik Cambria, Suhang Wang, Steffen Eger:
Graph routing between capsules. Neural Networks 143: 345-354 (2021) - [j17]Xuying Meng, Yequan Wang, Suhang Wang, Di Yao, Yujun Zhang:
Interactive Anomaly Detection in Dynamic Communication Networks. IEEE/ACM Trans. Netw. 29(6): 2602-2615 (2021) - [c77]Porter Jenkins, Ahmad Farag, J. Stockton Jenkins, Huaxiu Yao, Suhang Wang, Zhenhui Li:
Neural Utility Functions. AAAI 2021: 7917-7925 - [c76]Enyan Dai, Suhang Wang:
Towards Self-Explainable Graph Neural Network. CIKM 2021: 302-311 - [c75]Enyan Dai, Kai Shu, Yiwei Sun, Suhang Wang:
Labeled Data Generation with Inexact Supervision. KDD 2021: 218-226 - [c74]Enyan Dai, Charu Aggarwal, Suhang Wang:
NRGNN: Learning a Label Noise Resistant Graph Neural Network on Sparsely and Noisily Labeled Graphs. KDD 2021: 227-236 - [c73]Yao Ma, Suhang Wang, Tyler Derr, Lingfei Wu, Jiliang Tang:
Graph Adversarial Attack via Rewiring. KDD 2021: 1161-1169 - [c72]Teng Xiao, Zhengyu Chen, Donglin Wang, Suhang Wang:
Learning How to Propagate Messages in Graph Neural Networks. KDD 2021: 1894-1903 - [c71]Tsung-Yu Hsieh, Yiwei Sun, Suhang Wang, Vasant G. Honavar:
Functional Autoencoders for Functional Data Representation Learning. SDM 2021: 666-674 - [c70]Tsung-Yu Hsieh, Suhang Wang, Yiwei Sun, Vasant G. Honavar:
Explainable Multivariate Time Series Classification: A Deep Neural Network Which Learns to Attend to Important Variables As Well As Time Intervals. WSDM 2021: 607-615 - [c69]Enyan Dai, Suhang Wang:
Say No to the Discrimination: Learning Fair Graph Neural Networks with Limited Sensitive Attribute Information. WSDM 2021: 680-688 - [c68]Tianxiang Zhao, Xiang Zhang, Suhang Wang:
GraphSMOTE: Imbalanced Node Classification on Graphs with Graph Neural Networks. WSDM 2021: 833-841 - [c67]Tsung-Yu Hsieh, Yiwei Sun, Xianfeng Tang, Suhang Wang, Vasant G. Honavar:
SrVARM: State Regularized Vector Autoregressive Model for Joint Learning of Hidden State Transitions and State-Dependent Inter-Variable Dependencies from Multi-variate Time Series. WWW 2021: 2270-2280 - [i41]Zhilong Wang, Li Yu, Suhang Wang, Peng Liu:
Spotting Silent Buffer Overflows in Execution Trace through Graph Neural Network Assisted Data Flow Analysis. CoRR abs/2102.10452 (2021) - [i40]Tianxiang Zhao, Xiang Zhang, Suhang Wang:
GraphSMOTE: Imbalanced Node Classification on Graphs with Graph Neural Networks. CoRR abs/2103.08826 (2021) - [i39]Tianxiang Zhao, Xianfeng Tang, Xiang Zhang, Suhang Wang:
Semi-Supervised Graph-to-Graph Translation. CoRR abs/2103.08827 (2021) - [i38]Tianxiang Zhao, Enyan Dai, Kai Shu, Suhang Wang:
You Can Still Achieve Fairness Without Sensitive Attributes: Exploring Biases in Non-Sensitive Features. CoRR abs/2104.14537 (2021) - [i37]Yuqing Hu, Xiaoyuan Cheng, Suhang Wang, Jianli Chen, Tianxiang Zhao, Enyan Dai:
Times Series Forecasting for Urban Building Energy Consumption Based on Graph Convolutional Network. CoRR abs/2105.13399 (2021) - [i36]Enyan Dai, Charu C. Aggarwal, Suhang Wang:
NRGNN: Learning a Label Noise-Resistant Graph Neural Network on Sparsely and Noisily Labeled Graphs. CoRR abs/2106.04714 (2021) - [i35]Enyan Dai, Kai Shu, Yiwei Sun, Suhang Wang:
Labeled Data Generation with Inexact Supervision. CoRR abs/2106.04716 (2021) - [i34]Yang Li, Wei Zhao, Erik Cambria, Suhang Wang, Steffen Eger:
Graph Routing between Capsules. CoRR abs/2106.11531 (2021) - [i33]Wenqi Fan, Wei Jin, Xiaorui Liu, Han Xu, Xianfeng Tang, Suhang Wang, Qing Li, Jiliang Tang, Jianping Wang, Charu C. Aggarwal:
Jointly Attacking Graph Neural Network and its Explanations. CoRR abs/2108.03388 (2021) - [i32]Enyan Dai, Suhang Wang:
Towards Self-Explainable Graph Neural Network. CoRR abs/2108.12055 (2021) - [i31]Enyan Dai, Zhimeng Guo, Suhang Wang:
Label-Wise Message Passing Graph Neural Network on Heterophilic Graphs. CoRR abs/2110.08128 (2021) - 2020
- [j16]Kai Shu, Deepak Mahudeswaran, Suhang Wang, Dongwon Lee, Huan Liu:
FakeNewsNet: A Data Repository with News Content, Social Context, and Spatiotemporal Information for Studying Fake News on Social Media. Big Data 8(3): 171-188 (2020) - [j15]Yang Li, Suhang Wang, Yukun Ma, Quan Pan, Erik Cambria:
Popularity prediction on vacation rental websites. Neurocomputing 412: 372-380 (2020) - [c66]Xianfeng Tang, Huaxiu Yao, Yiwei Sun, Charu C. Aggarwal, Prasenjit Mitra, Suhang Wang:
Joint Modeling of Local and Global Temporal Dynamics for Multivariate Time Series Forecasting with Missing Values. AAAI 2020: 5956-5963 - [c65]Huaxiu Yao, Chuxu Zhang, Ying Wei, Meng Jiang, Suhang Wang, Junzhou Huang, Nitesh V. Chawla, Zhenhui Li:
Graph Few-Shot Learning via Knowledge Transfer. AAAI 2020: 6656-6663 - [c64]Xianfeng Tang, Huaxiu Yao, Yiwei Sun, Yiqi Wang, Jiliang Tang, Charu C. Aggarwal, Prasenjit Mitra, Suhang Wang:
Investigating and Mitigating Degree-Related Biases in Graph Convoltuional Networks. CIKM 2020: 1435-1444 - [c63]Tianxiang Zhao, Xianfeng Tang, Xiang Zhang, Suhang Wang:
Semi-Supervised Graph-to-Graph Translation. CIKM 2020: 1863-1872 - [c62]Lo Pang-Yun Ting, Shan-Yun Teng, Suhang Wang, Kun-Ta Chuang, Huan Liu:
Learning Latent Perception Graphs for Personalized Unknowns Recommendation. CogMI 2020: 32-41 - [c61]Thai Le, Suhang Wang, Dongwon Lee:
MALCOM: Generating Malicious Comments to Attack Neural Fake News Detection Models. ICDM 2020: 282-291 - [c60]Wentao Wang, Tyler Derr, Yao Ma, Suhang Wang, Hui Liu, Zitao Liu, Jiliang Tang:
Learning from Incomplete Labeled Data via Adversarial Data Generation. ICDM 2020: 1316-1321 - [c59]Kai Shu, Deepak Mahudeswaran, Suhang Wang, Huan Liu:
Hierarchical Propagation Networks for Fake News Detection: Investigation and Exploitation. ICWSM 2020: 626-637 - [c58]Enyan Dai, Yiwei Sun, Suhang Wang:
Ginger Cannot Cure Cancer: Battling Fake Health News with a Comprehensive Data Repository. ICWSM 2020: 853-862 - [c57]Wei Jin, Yao Ma, Xiaorui Liu, Xianfeng Tang, Suhang Wang, Jiliang Tang:
Graph Structure Learning for Robust Graph Neural Networks. KDD 2020: 66-74 - [c56]Thai Le, Suhang Wang, Dongwon Lee:
GRACE: Generating Concise and Informative Contrastive Sample to Explain Neural Network Model's Prediction. KDD 2020: 238-248 - [c55]Limeng Cui, Haeseung Seo, Maryam Tabar, Fenglong Ma, Suhang Wang, Dongwon Lee:
DETERRENT: Knowledge Guided Graph Attention Network for Detecting Healthcare Misinformation. KDD 2020: 492-502 - [c54]Xianfeng Tang, Yozen Liu, Neil Shah, Xiaolin Shi, Prasenjit Mitra, Suhang Wang:
Knowing your FATE: Friendship, Action and Temporal Explanations for User Engagement Prediction on Social Apps. KDD 2020: 2269-2279 - [c53]Suhang Wang, Chen Wang, Jian Xu:
Exploiting Bluetooth to Enquire Close Contacts Without Privacy Leakage. ML4CS (1) 2020: 366-375 - [c52]Wentao Wang, Suhang Wang, Wenqi Fan, Zitao Liu, Jiliang Tang:
Global-and-Local Aware Data Generation for the Class Imbalance Problem. SDM 2020: 307-315 - [c51]Kai Shu, Liangda Li, Suhang Wang, Yunhong Zhou, Huan Liu:
Joint Local and Global Sequence Modeling in Temporal Correlation Networks for Trending Topic Detection. WebSci 2020: 335-344 - [c50]Dongsheng Luo, Jingchao Ni, Suhang Wang, Yuchen Bian, Xiong Bill Yu, Xiang Zhang:
Deep Multi-Graph Clustering via Attentive Cross-Graph Association. WSDM 2020: 393-401 - [c49]Xianfeng Tang, Yandong Li, Yiwei Sun, Huaxiu Yao, Prasenjit Mitra, Suhang Wang:
Transferring Robustness for Graph Neural Network Against Poisoning Attacks. WSDM 2020: 600-608 - [c48]Yiwei Sun, Suhang Wang, Xianfeng Tang, Tsung-Yu Hsieh, Vasant G. Honavar:
Adversarial Attacks on Graph Neural Networks via Node Injections: A Hierarchical Reinforcement Learning Approach. WWW 2020: 673-683 - [i30]Kai Shu, Suhang Wang, Dongwon Lee, Huan Liu:
Mining Disinformation and Fake News: Concepts, Methods, and Recent Advancements. CoRR abs/2001.00623 (2020) - [i29]Enyan Dai, Yiwei Sun, Suhang Wang:
Ginger Cannot Cure Cancer: Battling Fake Health News with a Comprehensive Data Repository. CoRR abs/2002.00837 (2020) - [i28]Wei Jin, Yao Ma, Xiaorui Liu, Xianfeng Tang, Suhang Wang, Jiliang Tang:
Graph Structure Learning for Robust Graph Neural Networks. CoRR abs/2005.10203 (2020) - [i27]Xianfeng Tang, Yozen Liu, Neil Shah, Xiaolin Shi, Prasenjit Mitra, Suhang Wang:
Knowing your FATE: Friendship, Action and Temporal Explanations for User Engagement Prediction on Social Apps. CoRR abs/2006.06427 (2020) - [i26]Wei Jin, Tyler Derr, Haochen Liu, Yiqi Wang, Suhang Wang, Zitao Liu, Jiliang Tang:
Self-supervised Learning on Graphs: Deep Insights and New Direction. CoRR abs/2006.10141 (2020) - [i25]Xianfeng Tang, Huaxiu Yao, Yiwei Sun, Yiqi Wang, Jiliang Tang, Charu C. Aggarwal, Prasenjit Mitra, Suhang Wang:
Graph Convolutional Networks against Degree-Related Biases. CoRR abs/2006.15643 (2020) - [i24]Thai Le, Suhang Wang, Dongwon Lee:
MALCOM: Generating Malicious Comments to Attack Neural Fake News Detection Models. CoRR abs/2009.01048 (2020) - [i23]Enyan Dai, Suhang Wang:
FairGNN: Eliminating the Discrimination in Graph Neural Networks with Limited Sensitive Attribute Information. CoRR abs/2009.01454 (2020) - [i22]Tsung-Yu Hsieh, Suhang Wang, Yiwei Sun, Vasant G. Honavar:
Explainable Multivariate Time Series Classification: A Deep Neural Network Which Learns To Attend To Important Variables As Well As Informative Time Intervals. CoRR abs/2011.11631 (2020)
2010 – 2019
- 2019
- [j14]Yang Li, Quan Pan, Suhang Wang, Haiyun Peng, Tao Yang, Erik Cambria:
Disentangled Variational Auto-Encoder for semi-supervised learning. Inf. Sci. 482: 73-85 (2019) - [j13]Yang Li, Suhang Wang, Quan Pan, Haiyun Peng, Tao Yang, Erik Cambria:
Learning binary codes with neural collaborative filtering for efficient recommendation systems. Knowl. Based Syst. 172: 64-75 (2019) - [j12]Xuying Meng, Suhang Wang, Kai Shu, Jundong Li, Bo Chen, Huan Liu, Yujun Zhang:
Towards privacy preserving social recommendation under personalized privacy settings. World Wide Web 22(6): 2853-2881 (2019) - [c47]Shuo Yang, Kai Shu, Suhang Wang, Renjie Gu, Fan Wu, Huan Liu:
Unsupervised Fake News Detection on Social Media: A Generative Approach. AAAI 2019: 5644-5651 - [c46]Limeng Cui, Suhang Wang, Dongwon Lee:
SAME: sentiment-aware multi-modal embedding for detecting fake news. ASONAM 2019: 41-48 - [c45]Kai Shu, Xinyi Zhou, Suhang Wang, Reza Zafarani, Huan Liu:
The role of user profiles for fake news detection. ASONAM 2019: 436-439 - [c44]Suhang Wang, Charu C. Aggarwal, Huan Liu:
Beyond word2vec: Distance-graph Tensor Factorization for Word and Document Embeddings. CIKM 2019: 1041-1050 - [c43]Porter Jenkins, Ahmad Farag, Suhang Wang, Zhenhui Li:
Unsupervised Representation Learning of Spatial Data via Multimodal Embedding. CIKM 2019: 1993-2002 - [c42]Tian Shi, Vineeth Rakesh, Suhang Wang, Chandan K. Reddy:
Document-Level Multi-Aspect Sentiment Classification for Online Reviews of Medical Experts. CIKM 2019: 2723-2731 - [c41]Limeng Cui, Kai Shu, Suhang Wang, Dongwon Lee, Huan Liu:
dEFEND: A System for Explainable Fake News Detection. CIKM 2019: 2961-2964 - [c40]Ghazaleh Beigi, Kai Shu, Ruocheng Guo, Suhang Wang, Huan Liu:
Privacy Preserving Text Representation Learning. HT 2019: 275-276 - [c39]Tsung-Yu Hsieh, Yiwei Sun, Suhang Wang, Vasant G. Honavar:
Adaptive Structural Co-regularization for Unsupervised Multi-view Feature Selection. ICBK 2019: 87-96 - [c38]Yiwei Sun, Suhang Wang, Tsung-Yu Hsieh, Xianfeng Tang, Vasant G. Honavar:
MEGAN: A Generative Adversarial Network for Multi-View Network Embedding. IJCAI 2019: 3527-3533 - [c37]Kai Shu, Limeng Cui, Suhang Wang, Dongwon Lee, Huan Liu:
dEFEND: Explainable Fake News Detection. KDD 2019: 395-405 - [c36]Yao Ma, Suhang Wang, Charu C. Aggarwal, Jiliang Tang:
Graph Convolutional Networks with EigenPooling. KDD 2019: 723-731 - [c35]Yao Ma, Suhang Wang, Charu C. Aggarwal, Dawei Yin, Jiliang Tang:
Multi-dimensional Graph Convolutional Networks. SDM 2019: 657-665 - [c34]Kai Shu, Suhang Wang, Huan Liu:
Beyond News Contents: The Role of Social Context for Fake News Detection. WSDM 2019: 312-320 - [c33]Vineeth Rakesh, Suhang Wang, Kai Shu, Huan Liu:
Linked Variational AutoEncoders for Inferring Substitutable and Supplementary Items. WSDM 2019: 438-446 - [i21]Kai Shu, Deepak Mahudeswaran, Suhang Wang, Huan Liu:
Hierarchical Propagation Networks for Fake News Detection: Investigation and Exploitation. CoRR abs/1903.09196 (2019) - [i20]Yao Ma, Suhang Wang, Charu C. Aggarwal, Jiliang Tang:
Graph Convolutional Networks with EigenPooling. CoRR abs/1904.13107 (2019) - [i19]Kai Shu, Xinyi Zhou, Suhang Wang, Reza Zafarani, Huan Liu:
The Role of User Profile for Fake News Detection. CoRR abs/1904.13355 (2019) - [i18]