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2020 – today
- 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 - [i49]Enyan Dai, Wei Jin, Hui Liu, Suhang Wang:
Towards Robust Graph Neural Networks for Noisy Graphs with Sparse Labels. CoRR abs/2201.00232 (2022) - [i48]Tianxiang Zhao, Xiang Zhang, Suhang Wang:
Exploring Edge Disentanglement for Node Classification. CoRR abs/2202.11245 (2022) - [i47]Huaisheng Zhu, Suhang Wang:
Learning Fair Models without Sensitive Attributes: A Generative Approach. CoRR abs/2203.16413 (2022) - [i46]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) - [i45]Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang:
On Consistency in Graph Neural Network Interpretation. CoRR abs/2205.13733 (2022) - [i44]Teng Xiao, Zhengyu Chen, Zhimeng Guo, Zeyang Zhuang, Suhang Wang:
Decoupled Self-supervised Learning for Non-Homophilous Graphs. CoRR abs/2206.03601 (2022) - [i43]Teng Xiao, Zhengyu Chen, Suhang Wang:
Towards Bridging Algorithm and Theory for Unbiased Recommendation. CoRR abs/2206.03851 (2022) - [i42]Tianxiang Zhao, Xiang Zhang, Suhang Wang:
Synthetic Over-sampling for Imbalanced Node Classification with Graph Neural Networks. CoRR abs/2206.05335 (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 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]Yao Ma, Suhang Wang, Lingfei Wu, Jiliang Tang:
Attacking Graph Convolutional Networks via Rewiring. CoRR abs/1906.03750 (2019) - [i17]Ghazaleh Beigi, Kai Shu, Ruocheng Guo, Suhang Wang, Huan Liu:
I Am Not What I Write: Privacy Preserving Text Representation Learning. CoRR abs/1907.03189 (2019) - [i16]Xianfeng Tang, Yandong Li, Yiwei Sun, Huaxiu Yao, Prasenjit Mitra, Suhang Wang:
Robust Graph Neural Network Against Poisoning Attacks via Transfer Learning. CoRR abs/1908.07558 (2019) - [i15]Yiwei Sun, Suhang Wang, Tsung-Yu Hsieh, Xianfeng Tang, Vasant G. Honavar:
MEGAN: A Generative Adversarial Network for Multi-View Network Embedding. CoRR abs/1909.01084 (2019) - [i14]Yiwei Sun, Suhang Wang, Xianfeng Tang, Tsung-Yu Hsieh, Vasant G. Honavar:
Node Injection Attacks on Graphs via Reinforcement Learning. CoRR abs/1909.06543 (2019) - [i13]Huaxiu Yao, Chuxu Zhang, Ying Wei, Meng Jiang, Suhang Wang, Junzhou Huang, Nitesh V. Chawla, Zhenhui Li:
Graph Few-shot Learning via Knowledge Transfer. CoRR abs/1910.03053 (2019) - [i12]Thai Le, Suhang Wang, Dongwon Lee:
Why X rather than Y? Explaining Neural Model' Predictions by Generating Intervention Counterfactual Samples. CoRR abs/1911.02042 (2019) - [i11]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. CoRR abs/1911.10273 (2019) - 2018
- [j11]Jundong Li, Kewei Cheng, Suhang Wang, Fred Morstatter, Robert P. Trevino, Jiliang Tang, Huan Liu:
Feature Selection: A Data Perspective. ACM Comput. Surv. 50(6): 94:1-94:45 (2018) - [j10]Yang Li, Quan Pan, Suhang Wang, Tao Yang, Erik Cambria:
A Generative Model for category text generation. Inf. Sci. 450: 301-315 (2018) - [j9]Suhas Ranganath, Xia Hu, Jiliang Tang, Suhang Wang, Huan Liu:
Understanding and Identifying Rhetorical Questions in Social Media. ACM Trans. Intell. Syst. Technol. 9(2): 17:1-17:22 (2018) - [j8]Suhang Wang, Charu C. Aggarwal, Huan Liu:
Random-Forest-Inspired Neural Networks. ACM Trans. Intell. Syst. Technol. 9(6): 69:1-69:25 (2018) - [j7]Suhang Wang, Jiliang Tang, Yilin Wang, Huan Liu:
Exploring Hierarchical Structures for Recommender Systems. IEEE Trans. Knowl. Data Eng. 30(6): 1022-1035 (2018) - [c32]Xuying Meng, Suhang Wang, Huan Liu, Yujun Zhang:
Exploiting Emotion on Reviews for Recommender Systems. AAAI 2018: 3788-3795 - [c31]Xuying Meng, Suhang Wang, Kai Shu, Jundong Li, Bo Chen, Huan Liu, Yujun Zhang:
Personalized Privacy-Preserving Social Recommendation. AAAI 2018: 3796-3803 - [c30]Kai Shu, Suhang Wang, Huan Liu, Jiliang Tang, Yi Chang, Ping Luo:
Exploiting User Actions for App Recommendations. ASONAM 2018: 139-142 - [c29]Yao Ma, Suhang Wang, Jiliang Tang:
Local and Global Information Preserved Network Embedding. ASONAM 2018: 222-225 - [c28]Kai Shu, Suhang Wang, Thai Le, Dongwon Lee, Huan Liu:
Deep Headline Generation for Clickbait Detection. ICDM 2018: 467-476 - [c27]Fan Yang, Ninghao Liu, Suhang Wang, Xia Hu:
Towards Interpretation of Recommender Systems with Sorted Explanation Paths. ICDM 2018: 667-676 - [c26]Wen Zhang, Kai Shu, Suhang Wang, Huan Liu, Yalin Wang:
Multimodal Fusion of Brain Networks with Longitudinal Couplings. MICCAI (3) 2018: 3-11 - [c25]Kai Shu, Suhang Wang, Huan Liu:
Understanding User Profiles on Social Media for Fake News Detection. MIPR 2018: 430-435 - [c24]Yilin Wang, Suhang Wang, Guojun Qi, Jiliang Tang, Baoxin Li:
Weakly Supervised Facial Attribute Manipulation via Deep Adversarial Network. WACV 2018: 112-121 - [c23]Kai Shu, Suhang Wang, Jiliang Tang, Yilin Wang, Huan Liu:
CrossFire: Cross Media Joint Friend and Item Recommendations. WSDM 2018: 522-530 - [i10]Yao Ma, Suhang Wang, Charu C. Aggarwal, Dawei Yin, Jiliang Tang:
Multi-dimensional Graph Convolutional Networks. CoRR abs/1808.06099 (2018) - [i9]Kai Shu, Deepak Mahudeswaran, Suhang Wang, Dongwon Lee, Huan Liu:
FakeNewsNet: A Data Repository with News Content, Social Context and Dynamic Information for Studying Fake News on Social Media. CoRR abs/1809.01286 (2018) - 2017
- [j6]Yang Li, Quan Pan, Tao Yang, Suhang Wang, Jiliang Tang, Erik Cambria:
Learning Word Representations for Sentiment Analysis. Cogn. Comput. 9(6): 843-851 (2017) - [j5]Kai Shu, Amy Sliva, Suhang Wang, Jiliang Tang, Huan Liu:
Fake News Detection on Social Media: A Data Mining Perspective. SIGKDD Explor. 19(1): 22-36 (2017) - [j4]Suhas Ranganath, Suhang Wang, Xia Hu, Jiliang Tang, Huan Liu:
Facilitating Time Critical Information Seeking in Social Media. IEEE Trans. Knowl. Data Eng. 29(10): 2197-2209 (2017) - [c22]Yilin Wang, Suhang Wang, Jiliang Tang, Guo-Jun Qi, Huan Liu, Baoxin Li:
CLARE: A Joint Approach to Label Classification and Tag Recommendation. AAAI 2017: 210-216 - [c21]Suhang Wang, Charu C. Aggarwal, Jiliang Tang, Huan Liu:
Attributed Signed Network Embedding. CIKM 2017: 137-146 - [c20]Yao Ma, Suhang Wang, Jiliang Tang:
Network Embedding with Centrality Information. ICDM Workshops 2017: 1144-1145 - [c19]Suhang Wang, Charu C. Aggarwal, Huan Liu:
Randomized Feature Engineering as a Fast and Accurate Alternative to Kernel Methods. KDD 2017: 485-494 - [c18]Suhang Wang, Charu C. Aggarwal, Huan Liu:
Using a Random Forest to Inspire a Neural Network and Improving on It. SDM 2017: 1-9 - [c17]Suhang Wang, Jiliang Tang, Charu C. Aggarwal, Yi Chang, Huan Liu:
Signed Network Embedding in Social Media. SDM 2017: 327-335 - [c16]Yang Li, Suhang Wang, Tao Yang, Quan Pan, Jiliang Tang:
Price Recommendation on Vacation Rental Websites. SDM 2017: 399-407 - [c15]Suhang Wang, Yilin Wang, Jiliang Tang,