Publications
Book or Book Chapters
- Deep Generative Models for Recommender Systems
[pdf]
Vineeth Rakesh, Suhang Wang and Huan Liu
Big Data Recommender Systems, IET, 2018
- Deep Learning for Feature Representation
[pdf]
Suhang Wang and Huan Liu
Feature Engineering for Machine Learning and Data Analytics, CRC Press, 2018
- Feature Selection
[pdf]
Suhang Wang, Jiliang Tang and Huan Liu
Encyclopedia of Machine Learning and Data Mining DOI:10.1007/978-1-4899-7502-7_101-1, 2016
Journal Papers
- Imbalanced Node Classification with Synthetic Over-sampling
[pdf]
Tianxiang Zhao, Xiang Zhang, and Suhang Wang ACM TKDE, 2024
- Towards Prototype-Based Self-Explainable Graph Neural Network
[pdf]
Enyan Dai, and Suhang Wang ACM TKDD
- A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainability
[pdf]
Enyan Dai, Tianxiang Zhoa, Huaisheng Zhu, Junjie Xu, Zhimeng Guo, Hui Liu, Jiliang Tang, and Suhang Wang Machine Intelligence Research, 2024
- Recent Developments in Recommender Systems: A Survey
[pdf]
Yang Li, Kangbo Liu, Ranjan Satapathy, Suhang Wang, and Erik Cambria. IEEE Computational Intelligence Magazine, 2024
- Counterfactual Learning on Graphs: A Survey
[pdf]
Zhimeng Guo, Zongyu Wu, Teng Xiao, Charu Aggarwal, Hui Liu, and Suhang Wang. Machine Intelligence Research, 2024
- Faithful and Consistent Graph Neural Network Explanations with Rationale Alignment
[pdf]
Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, and Suhang Wang ACM TIST, 2023
- Learning Fair Models without Sensitive Attributes: A Generative Approach
[pdf]
Huaisheng Zhu, Enyan Dai, Hui Liu, and Suhang Wang Neurocomputing, 2023
- Learning Fair Graph Neural Networks with Limited and Private Sensitive Attribute Information
[pdf]
Enyan Dai, Suhang Wang IEEE TKDE, 2022
- Times Series Forecasting for Urban Building Energy Consumption Based on Graph Convolutional Network
[pdf]
Yuqing Hu, Xiaoyuan Cheng, Suhang Wang, Jianli Chen, Tianxiang Zhao, Enyan Dai. Applied Energy, 2022
- Interactive Anomaly Detection in Dynamic Communication Networks
[pdf]
Xuying Meng, Yequan Wang, Suhang Wang, Di Yao, and Yujun Zhang. IEEE/ACM TON, 2021
- Semi-supervised Anomaly Detection in Dynamic Communication Networks
[pdf]
Xuying Meng, Suhang Wang, Zhimin Liang, Di Yao, Jihua Zhou, and Yujun Zhang. Information Sciences, 2021
- Graph Routing Between Capsules
[pdf]
Yang Li, Wei Zhao, Eric Cambria, Suhang Wang, and Steffen Eger. Neural Networks, 2021
- Integrating Multimodal and Longitudinal Neuroimaging Data with Multisource Network Representation learning
[pdf]
Wen Zhang, Brittany Blair Barden, Gustavo Miranda, Kai Shu, Suhang Wang, Huan Liu, and Yalin Wang. Neuroinformatics, 2021
- Popularity Prediction on Vacation Rental Websites
[pdf]
Yang Li, Suhang Wang, Yukun Ma , Quan Pan, and Eric Cambria. Neurocomputing, 2020
- FakeNewsNet: A Data Repository with News Content, Social Context, and Spatiotemporal Information for Studying Fake News on Social Media
[pdf]
Kai Shu, Deepak Mahudeswaran, Suhang Wang, Dongwon Lee, and Huan Liu. Big Data, 2020
- Learning Binary Codes with Neural Collaborative Filtering for Efficient Recommendation Systems
[pdf]
Yang Li, Suhang Wang, Quan Pan, Haiyun Peng, Tao Yang, and Eric Cambria. Knowledge-Based Systems, 2019
- Disentangled Variational Auto-Encoder for Semi-supervised Learning
[pdf]
Yang Li, Quan Pan, Suhang Wang, Haiyun Peng, Tao Yang, and Eric Cambria. Information Sciences, 2019
- Random-Forest Inspired Neural Networks
[pdf]
Suhang Wang, Charu Aggarwal and Huan Liu. ACM TIST, 2018
- Towards Privacy Preserving Social Recommendation under Personalized Privacy Settings
[pdf]
Xuying Meng, Suhang Wang, Kai Shu, Jundong Li, Bo Chen, Huan Liu, Yujun Zhang. World Wide Web Journal, 2018
- A Generative Model for Category Text Generation
[pdf]
Yang Li, Quan Pan, Suhang Wang, Tao Yang, and Erik Cambria. Information Sciences, 2018
- Exploring Hierarchical Structures for Recommender Systems
[pdf]
Suhang Wang, Jiliang Tang, Yilin Wang and Huan Liu. IEEE TKDE, 2018
- Learning Word Representations for Sentiment Analysis
[pdf]
Yang Li, Quan Pan, Tao Yang, Suhang Wang, Jiliang Tang, and Erik Cambria. Springer Cognitive Computation, 2017
- Fake News Detection on Social Media: A Data Mining Perspective
[pdf]
Kai Shu, Amy Sliva, Suhang Wang, Jiliang Tang, and Huan Liu. SIGKDD Explorations, 2017
- Understanding and Identifying Rhetorical Questions in Social Media
[pdf]
Suhas Ranganath, Xia Hu, Jiliang Tang, Suhang Wang and Huan Liu. ACM TIST, 2017
- Facilitating Time Critical Information Seeking in Social Media
[pdf]
Suhas Ranganath, Suhang Wang, Xia Hu, Jiliang Tang and Huan Liu. IEEE TKDE, 2017
- User Identity Linkage across Online Social Netwroks: A Review
[pdf]
Kai Shu, Suhang Wang, Jiliang Tang, Reza Zafarani and Huan Liu. SIGKDD Explorations, December, 2016
- Enhanced Low-rank Representation via Sparse Manifold Adaption for
Semi-supervised Learning
[pdf][code]
Yong Peng, Bao-Liang Lu and Suhang Wang. Neural
Networks, DOI: 10.1016/j.neunet.2015.01.001, 2015
- Discriminative Graph Regularized Extreme Learning Machine and Its
Application to Face Recognition
[pdf][code]
Yong
Peng, Suhang Wang, Xianzhong Long and Bao-Liang Lu. Neurocomputing,
149: 340-353, 2015
Conference Publications
2024
- HC-GST: Heterophilyaware Distribution Consistency based Graph Self-training
[pdf]
FaliWang, Tianxiang Zhao, Junjie Xu, and Suhang Wang
In Proceedings of 33rd ACM International Conference on Information and Knowledge Management (CIKM 2024)
- Shapeaware Graph Spectral Learning
[pdf]
Junjie Xu, Enyan Dai, Dongsheng Luo, Xiang Zhang, and Suhang Wang
In Proceedings of 33rd ACM International Conference on Information and Knowledge Management (CIKM 2024)
- Comprehensive Feature Attributions: Inherently Explainable Model with Background Supervision
[pdf]
Xianren Zhang, Dongwon Lee, and Suhang Wang
In Proceedings of the 18th European Conference on Computer Vision (ECCV 2024)
- Rethinking Graph Backdoor Attacks: A Distribution-Preserving Perspective
[pdf]
Zhiwei Zhang, Minhua Lin, Enyan Dai, and Suhang Wang
In Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2024)
- Multi-source Unsupervised Domain Adaptation for Graphs.
[pdf]
Tianxiang Zhao, Donghsneg Luo, Xiang Zhang, and Suhang Wang
In Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2024)
- Addressing Shortcomings in Fair Graph Learning Datasets: Towards a New Benchmark
[pdf]
Xiaowei Qian, Zhimeng Guo, Jialiang Li, Haitao Mao, Bingheng Li, Suhang Wang, Yao Ma
In Proceedings of 30th SIGKDD Conference on Knowledge Discovery and Data Mining - Applied Data Science Track (KDD 2024 - ADS)
- Graph Chainof-Thought: Augmenting Large Language Models by Reasoning on Graphs
[pdf]
Bowen Jin, Chulin Xie, Jiawei Zhang, Kashob Kumar Roy, Yu Zhang, Zheng Li, Ruirui Li, Xianfeng Tang, Suhang Wang, Yu Meng, Jiawei Han
In Proceedings of Findings of the 62nd Annual Meeting of the Association for Computational Linguistics (Findings of ACL 2024)
- Language Models As Semantic Indexers
[pdf]
Bowen Jin, Hansi Zeng, GuoyinWang, Xiusi Chen, TianxinWei, Ruirui Li, Zhengyang Wang, Zheng Li, Yang Li, Hanqing Lu, Suhang Wang, Jiawei Han, Xianfeng
Tang
In Proceedings of the Forty-first International Conference on Machine Learning (ICML 2024)
- Efficient Contrastive Learning for Fast andAccurate Inference on Graphs
[pdf]
Teng Xiao, Huaisheng Zhu, Zhiwei Zhang, Zhimeng Guo, Charu C Aggarwal, Suhang Wang, and Vasant Honavar
In Proceedings of the Forty-first International Conference on Machine Learning (ICML 2024)
- Universal Prompt Optimizer for Safe Text-to-Image Generation
[pdf]
Zongyu Wu, Hongcheng Gao, Yueze Wang, Xiang Zhang, and Suhang Wang
In Proceedings of the 2024 Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL 2024)
- Disambiguated Node Classification with Graph Neural Networks
[pdf]
Tianxiang Zhao, Xiang Zhang, and Suhang Wang
In Proceedings of the Web Conference (WWW 2024)
- Hierarchical Query Classification in E-commerce Search
[pdf]
Bing He, Sreyashi Nag, Limeng Cui, Suhang Wang, Zheng Li, Rahul Goutam, Zhen Li and Haiyang Zhang
In Proceedings of the Web Conference (WWW 2024 Industry Track)
- AmGNN: A Framework for Adaptive Processing of Inter-layer Information in Multi-layer Graph
[pdf]
Huaisheng Zhu, Zongyu Wu, Tianxiang Zhao, and Suhang Wang
In Proceedings of 16th International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2024)
- Towards Universal Multi-Modal Personalization: A Language Model Empowered Generative Paradigm
[pdf]
Tianxin Wei, Bowen Jin, Ruirui Li, Hansi Zeng, Zhengyang Wang, Jianhui Sun, Qingyu Yin, Hanqing Lu, Suhang Wang, Jingrui He, Xianfeng Tang
In Proceedings of the Twelfth International Conference on Learning Representations (ICLR 2024)
- Active Learning for Graphs with Noisy Structures
[pdf]
Hongliang Chi, Cong Qi, Suhang Wang, Yao Ma
In Proceedings of the Twenty-Fourth SIAM International Conference on Data Mining (SDM 2024)
- Spectral-based Graph Neutral Networks for Complementary Item Recommendation
[pdf]
Haitong Luo, Xuying Meng, Suhang Wang, Hanyun Cao, Weiyao Zhang, Yequan Wang, Yujun Zhang
In Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence (AAAI 2024)
- LightLT: a Lightweight Representation Quantization Framework for Long-tail Data
[pdf]
Haoyu Wang, Ruirui Li, Zhengyang Wang, Xianfeng Tang, Danqing Zhang, Monica Cheng, Bing Yin, Jasha Droppo, Suhang Wang, and Jing Gao
In Proceedings of the 40th IEEE International Conference on Data Engineering (ICDE 2024)
- Distribution Consistency based Self-Training for Graph Neural Networks with Sparse Labels
[pdf]
Fali Wang, Tianxiang Zhao, and Suhang Wang
In Proceedings of the 16th ACM International Conference on Web Search and Data Mining (WSDM 2024)
- Interpretable Imitation Learning with Dynamic Causal Relations
[pdf]
Tianxiang Zhao, Wenchao Yu, Suhang Wang, Lu Wang, Xiang Zhang, Yuncong Chen, Yanchi Liu, Wei Cheng, and Haifeng Chen
In Proceedings of the 16th ACM International Conference on Web Search and Data Mining (WSDM 2024)
2023
- Certifiably Robust Graph Contrastive Learning
[pdf]
Minhua Lin, Teng Xiao, Enyan Dai, and Suhang Wang
In Proceedings of Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS 2023)
- Simple Asymmetric Contrastive Learning of Graphs
[pdf]
Teng Xiao, Huaisheng Zhu, Zhengyu Chen, and Suhang Wang
In Proceedings of Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS 2023)
- Amazon-M2: A Multilingual Multi-locale Shopping Session Dataset for Recommendation and Text Generation
[pdf]
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
In Proceedings of NeurIPS 2023 Datasets and Benchmarks Track
- Towards Fair Graph Neural Networks via Graph Counterfactual
[pdf]
Zhimeng Guo, Jialiang Li, Teng Xiao, Yao Ma, and Suhang Wang
In Proceedings of 32nd ACM International Conference on Information and Knowledge Management (CIKM 2023)
- STAN: Stage-Adaptive Network for Multi-Task Recommendation by Learning User Lifecycle-Based Representation
[pdf]
Wanda Li, Wenhao Zheng, Xuanji Xiao, and Suhang Wang
In Proceedings of The 17th ACM Recommender Systems Conference (RecSys 2023)
- Reconsidering Learning Objectives in Unbiased Recommendation: A Distribution Shift Perspective.
[pdf]
Teng Xiao, Zhengyu Chen, and Suhang Wang
In Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2023)
- Skill Disentanglement for Imitation Learning from Suboptimal Demonstrations.
[pdf]
Tianxiang Zhao, Wenchao Yu, Suhang Wang, Lu Wang, Xiang Zhang, Yuncong Chen, Yanchi Liu, Wei Cheng, Haifeng Chen
In Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2023)
- A Unified Framework of Graph Information Bottleneck for Robustness and Membership Privacy.
[pdf]
Enyan Dai, Limeng Cui, Zhengyang Wang, Xianfeng Tang, Yinghan Wang, Monica Chen, Bing Yin, and Suhang Wang
In Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2023)
- Exploiting Intent Evolution in E-commercial Query Recommendation. >
[pdf]
Yu Wang, Zhengyang Wang, Hengrui Zhang, Qingyu Yin, Xianfeng Tang, Yinghan Wang, Danqing Zhang, Limeng Cui, Monica Cheng, Bing Yin, and Suhang Wang, Philip S Yu
In Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2023)
- Unnoticeable Backdoor Attacks on Graph Neural Networks
[pdf]
Enyan Dai, Minhua Lin, Xiang Zhang, and Suhang Wang
In Proceedings of the Web Conference (WWW 2023)
- Jointly Attacking Graph Neural Network and its Explanations
[pdf]
Wenqi Fan1, Han Xu, Wei Jin, Xiaorui Liu, Xianfeng Tang, Suhang Wang, Qing Li, Jiliang Tang, Jianping Wang, and Charu Aggarwal
In Proceedings of the 39th IEEE International Conference on Data Engineering (ICDE 2023)
- Towards Faithful and Consistent Explanations for Graph Neural Networks
[pdf]
Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, and Suhang Wang
In Proceedings of the 15th ACM International Conference on Web Search and Data Mining (WSDM 2023)
- You Need to Look Globally: Discovering Representative Topology Structures to Enhance Graph Neural Network
[pdf]
Huaisheng Zhu, Xianfeng Tang, Tianxiang Zhao, and Suhang Wang
In Proceedings of the 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD 2023)
2022
- TopoImb: Toward Topology-level Imbalance in Learning from Graphs
[pdf]
Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, and Suhang Wang
In Proceedings of the 1st Learning on Graphs Conference (LoG 2022)
- Label-Wise Graph Convolutional Network for Heterophilic Graphs
[pdf]
Enyan Dai, Shijie Zhou, Zhimeng Guo, and Suhang Wang
In Proceedings of the 1st Learning on Graphs Conference (LoG 2022)
- Decoupled Self-supervised Learning for Non-Homophilous Graphs
[pdf]
Teng Xiao, Zhengyu Chen, Zhimeng Guo, Zeyang Zhuang, and Suhang Wang
In Proceedings of Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS 2022)
- HP-GMN: Graph Memory Networks for Heterophilous Graphs
[pdf]
Junjie Xu, Enyan Dai, Xiang Zhang, and Suhang Wang
In Proceedings of 22nd ICDM IEEE International Conference on Data Mining (ICDM 2022)
- Representation Matters When Learning From Biased Feedback in Recommendation
[pdf]
Teng Xiao, Zhengyu Chen, and Suhang Wang
In Proceedings of 31st ACM International Conference on Information and Knowledge Management (CIKM 2022)
- Exploring Edge Disentanglement for Node Classification
[pdf]
Tianxiang Zhao, Xiang Zhang, and Suhang Wang
In Proceedings of the Web Conference (WWW 2022)
- Towards Off-Policy Learning for Ranking Policies with Logged Feedback
[pdf]
Teng Xiao, and Suhang Wang
In Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI 2022)
- Towards Robust Graph Neural Networks for Noisy Graphs with Sparse Labels
[pdf]
Enyan Dai, Jin Wei, Hui Liu, and Suhang Wang
In Proceedings of the 15th ACM International Conference on Web Search and Data Mining (WSDM 2022)
- Towards Fair Classifiers Without Sensitive Attributes: Exploring Biases in Related Features
[pdf]
Tianxiang Zhao, Enyan Dai, Kai Shu, and Suhang Wang
In Proceedings of the 15th ACM International Conference on Web Search and Data Mining (WSDM 2022)
- Towards Unbiased and Robust Causal Ranking for Recommender Systems
[pdf]
Teng Xiao, and Suhang Wang
In Proceedings of the 15th ACM International Conference on Web Search and Data Mining (WSDM 2022)
- Ranking Friend Stories on Social Platforms with Edge-Contextual Local Graph Convolutions
[pdf]
Xianfeng Tang, Yozen Liu, Xinran He, Suhang Wang, and Neil Shah
In Proceedings of the 15th ACM International Conference on Web Search and Data Mining (WSDM 2022)
2021
- Towards Self-Explaianble Graph Neural Networks.
[pdf]
Enyan Dai, and Suhang Wang
In Proceedings of 30th ACM International Conference on Information and Knowledge Management (CIKM-21)
- NRGNN: Learning a Label Noise Resistant Graph Neural Network on Sparsely and Noisily Labeled Graphs.
[pdf]
Enyan Dai, Charu Aggarwal, and Suhang Wang
In Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD-21)
- Learning How to Propagate Messages in Graph Neural Networks.
[pdf]
Teng Xiao, Zhengyu Chen, Donglin Wang and Suhang Wang
In Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD-21)
- Labeled Data Generation with Inexact Supervision.
[pdf]
Enyan Dai, Yiwei Sun, Kai Shu, and Suhang Wang
In Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD-21)
- Attacking Graph Convolutional Networks via Rewiring.
[pdf]
Yao Ma, Suhang Wang, Lingfei Wu, and Jiliang Tang
In Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD-21)
- SRVAR: Joint Discrete Hidden State Discovery and Structure Learning from Time Series Data
[pdf]
Tsung-Yu Hsieh, Yiwei Sun, Xianfeng Tang, Suhang Wang, and Vasant Honavar
In Proceedings of the Web Conference (WWW 2021)
- Functional Autoencoders for Functional Data Representation Learning
[pdf]
Tsung-Yu Hsieh, Yiwei Sun, Suhang Wang, and Vasant Honavar
In Proceedings of the Twenty-First SIAM International Conference on Data Mining (SDM-21)
- Neural Utility Functions
[pdf]
Porter Jenkins, Ahmad Farag, Stockton Jenkins, Huaxiu Yao, Suhang Wang, and Zhenhui Li
In Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI 2021)
- Say No to the Discrimination: Learning Fair Graph Neural Networks with Limited Sensitive Attribute Information
[pdf]
Enyan Dai, and Suhang Wang
In Proceedings of the 14th ACM International Conference on Web Search and Data Mining (WSDM 2021)
- GraphSMOTE: Imbalanced Node Classification on Graphs with Graph Neural Networks
[pdf]
Tianxiang Zhao, Xiang Zhang, and Suhang Wang
In Proceedings of the 14th ACM International Conference on Web Search and Data Mining (WSDM 2021)
- Explainable Multivariate Time Series: A Deep Neural Network Which Learns to Attend Important Variables As Well As Time Intervials
[pdf]
Tsung-Yu Hsieh, Suhang Wang, Yiwei Sun, and Vasant Honavar
In Proceedings of the 14th ACM International Conference on Web Search and Data Mining (WSDM 2021)
2020
- MALCOM: Generating Malicious Comments to Attack Neural Fake News Detection Modelss
[pdf]
Thai Le, Suhang Wang, and Dongwon Lee
In Proceedings of 20th ICDM IEEE International Conference on Data Mining (ICDM-20)
- Learning from Incomplete Labeled Data via Adversarial Data Generation
[pdf]
Wentao Wang, Tyler Derr, Yao Ma, Suhang Wang, Hui Liu, Zitao Liu, and Jiliang Tang
In Proceedings of 20th ICDM IEEE International Conference on Data Mining (ICDM-20)
- Investigating and Mitigating Degree-Related Biases in Graph Convolutional Networks
[pdf]
Xianfeng Tang, Huaxiu Yao, Yiwei Sun, Yiqi Wang, Jiliang Tang, Charu Aggarwal, Prasenjit Mitra, and Suhang Wang
In Proceedings of 29th ACM International Conference on Information and Knowledge Management (CIKM-20)
- Semi-Supervised Graph-to-Graph Translations
[pdf]
Tianxiang Zhao, Xianfeng Tang, Xiang Zhang, and Suhang Wang
In Proceedings of 29th ACM International Conference on Information and Knowledge Management (CIKM-20)
- Knowing Your FATE: Friendship, Action and Temporal Explanations for User Engagement Prediction on Social Apps
[pdf]
Xianfeng Tang, Yozen Liu, Neil Shah, Xiaolin Shi, Prasenjit Mitra, and Suhang Wang
In Proceedings of the 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD-20)
- Graph Structure Learning for Robust Graph Nerual Networks
[pdf]
Wei Jin, Yao Ma, Xiaorui Liu, Xianfeng Tang, Suhang Wang, and Jiliang Tang
In Proceedings of the 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD-20)
- GRACE: Generating Concise and Informative Constrastive Sample to Explain Neural Network Model's Prediction
[pdf]
Thai Le, Suhang Wang, and Dongwon Lee
In Proceedings of the 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD-20)
- DETERRENT: Knowledge Guided Graph Attention Network for Detecting Healthcare Misinformaiton
[pdf]
Limeng Cui, Haseseung Seo, Maryain Tabar, Fenglong Ma, Suhang Wang, and Dongwon Lee
In Proceedings of the 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD-20)
- Joint Local and Global Sequence Modeling in Temporal Correlation Network for Search Trending Topic Detection
[pdf]
Kai Shu, Liangda Li, Suhang Wang, Yunhong Zhou, and Huan Liu
In Proceedings of the 12th ACM Web Science Conference (Websci 2020)
- Ginger Cannot Cure Cancer: Battling Fake Health News with A Comprehensive Data Repository
[pdf]
Enyan Dai, Yiwei Sun, and Suhang Wang
In Proceedings of the Internatioal AAAI Conference on Web and Social Media (ICWSM-20)
- Node Injection Attack on Graphs via Reinforcement Learning
[pdf]
Yiwei Sun, Suhang Wang, Xianfeng Tang, Tsung-Yu Hsieh, and Vasant Honavar
In Proceedings of the Web Conference (WWW-20)
- Global-and-Local Aware Data Generation for the Class Imblance Problem
[pdf]
Wentao Wang, Suhang Wang, Wenqi Fan, Zitao Liu, and Jiliang Tang
In Proceedings of the Twentieth SIAM International Conference on Data Mining (SDM-20)
- Hierarchical Propagation Networks for Fake News Detection: Investigation and Exploitation
[pdf]
Kai Shu, Deepak Mahudaswaran, Suhang Wang, and Huan Liu
In Proceedings of the Internatioal AAAI Conference on Web and Social Media (ICWSM-20)
- Joint Modeling of Local and Global Temporal Dynamics of Multivariate Time Series Forecasting with Missing Values
[pdf]
Xianfeng Tang, Huaxiu Yao, Yiwei Sun, Charu Aggarwal, Prasenjit Mitra, and Suhang Wang
In Proceedings of the Thirty-Forth AAAI Conference on Artificial Intelligence (AAAI-20)
- Graph Few-shot Learning via Knowledge Transfer
[pdf]
Huaxiu Yao, Chuxu Zhang, Ying Wei, Meng Jiang, Suhang Wang, Junzhou Huang, Nitesh Chawla, Zhenhui Li
In Proceedings of the Thirty-Forth AAAI Conference on Artificial Intelligence (AAAI-20)
- Transferring Robustness for Graph Neural Network Against Poisoning Attacks
[pdf]
Xianfeng Tang, Yandong Li, Yiwei Sun, Huaxiu Yao, Prasenjit Mitra, and Suhang Wang
In Proceedings of the 13th ACM International Conference on Web Search and Data Mining (WSDM 2020)
- Deep Multi-Graph Clustering via Attentive Cross-Graph Association
[pdf]
Dongsheng Li, Jingchao Ni, Suhang Wang, Yuchen Bian, Xiong Yu and Xiang Zhang
In Proceedings of the 13th ACM International Conference on Web Search and Data Mining (WSDM 2020)
2019
- Document-Level Multi-Aspect Sentiment Classification for Online Reviews of Medical Docotors
[pdf]
Tian Shi, Vineeth Rakesh, Suhang Wang, Chandan K. Reddy
In Proceedings of 28th ACM International Conference on Information and Knowledge Management (CIKM-19)
- Beyond word2vec: Distance-graph Tensor Factorization for Word and Document Embeddings
[pdf]
Suhang Wang, Charu Aggarwal, and Huan Liu
In Proceedings of 28th ACM International Conference on Information and Knowledge Management (CIKM-19)
- Unsupervised Representation Learning of Spatial Data via Multimodal Embedding
[pdf]
Porter Jenkins, Ahmad Farag, Suhang Wang, and Zhenhui Li
In Proceedings of 28th ACM International Conference on Information and Knowledge Management (CIKM-19)
- SAME: Sentiment-Aware Multi-Modal Embedding for Detecting Fake News
[pdf]
Limeng Cui, Suhang Wang, and Dongwon Lee
In Proceedings of IEEE/ACM International Conference on Advances in Social Networks Analysis and Minings (ASONAM-19)
- The Role of User Profiles for Fake News Detection
[pdf]
Kai Shu, Xinyi Zhou, Suhang Wang, Reza Zafarani, and Huan Liu
In Proceedings of IEEE/ACM International Conference on Advances in Social Networks Analysis and Minings (ASONAM-19)
- Multi-View Network Embedding via Generative Adversarial Networks
[pdf]
Yiwei Sun, Suhang Wang, Tsung-Yu Hsieh, Xianfeng Tang, and Vasant Honavar
In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI-19)
- Graph Convolutional Networks with EigenPoolings
[pdf]
Yao Ma, Suhang Wang, Charu Aggarwal, and Jiliang Tang
In Proceedings of the 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD-19)
- dEFEND: Explainable Fake News Detection
[pdf]
Kai Shu, Limeng Cui, Suhang Wang, Dongwon Lee, and Huan Liu
In Proceedings of the 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD-19)
- Multi-dimensional Graph Convolutional Networks
[pdf]
Yao Ma, Suhang Wang, Charu Aggarwal, Dawei Yin, and Jiliang Tang
In Proceedings of the Nineteenth SIAM International Conference on Data Mining (SDM-19)
- Unsupervised Fake News Detection on Social Media: A Generative Approach
[pdf]
Shuo Yang, Kai Shu, Suhang Wang, Renjie Gu, Fan Wu, and Huan Liu
In Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-19)
- Linked Variational AutoEncoders for Inferring Substitutable and Supplementary Items
[pdf]
Vineeth Rakesh, Suhang Wang, Kai Shu, and Huan Liu
In Proceedings of the 12th ACM International Conference on Web Search and Data Mining (WSDM 2019)
- Beyond News Contents: The Role of Social Context for Fake News Detection
[pdf]
Kai Shu, Suhang Wang, and Huan Liu
In Proceedings of the 12th ACM International Conference on Web Search and Data Mining (WSDM 2019)
2018
- Deep Headline Generation for Clickbait Detection
[pdf]
Kai Shu, Suhang Wang, Thai Le, Dongwon Lee and Huan Liu
In Proceedings of the 2018 IEEE International Conference on Data Mining (ICDM-18), regular paper
- Towards Interpretation of Recommender Systems with Sorted Explanation Paths
[pdf]
Fan Yang, Ninghao Liu, Suhang Wang and Xia Hu
In Proceedings of the 2018 IEEE International Conference on Data Mining (ICDM-18), regular paper
- Local and Global Information Preserved Network Embeddings
[pdf]
Yao Ma, Suhang Wang, Jiliang Tang.
In Proceedings of the international conference series on Advances in Social Network Analysis and Mining (ASONAM-18), short paper
- Exploiting User Actions for App Recommendations
[pdf]
Kai Shu, Suhang Wang, Jiliang Tang, Yi Chang, Huan Liu.
In Proceedings of the international conference series on Advances in Social Network Analysis and Mining (ASONAM-18), short paper
- Multimodal Fusion of Brain Networks with Longitudinal Couplings
[pdf]
Wen Zhang, Kai Suhang, Suhang Wang, Huan Liu, Yalin Wang.
In Proceedings of the 21st International Conference On Medical Image Computing & Computer Assisted Intervention (MICCAI-18)
- Exploiting Emotion on Reviews for Recommender Systems
[pdf]
Xuying Meng, Suhang Wang, Huan Liu, Yujun Zhang.
In Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence (AAAI-18)
- Personalized Privacy-Preserving Social Recommendation
[pdf]
Xuying Meng, Suhang Wang, Kai Shu, Jundong Li, Bo Chen, Huan Liu, Yujun Zhang.
In Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence (AAAI-18)
- CrossFire: Cross Media Joint Item and Friend Recommendations
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Kai Shu, Suhang Wang, Jiliang Tang, Yilin Wang, Huan Liu.
In Proceedings of the 11th ACM International Conference on Web Search and Data Mining (WSDM 2018)
- Weakly Supervised Facial Attribute Manipulation via Deep Adversarial Network
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Yilin Wang, Suhang Wang, Guojun Qi, Jiliang Tang, Baoxin Li.
In Proceedings of the IEEE Winter Conference on Applications of Computer Vision (WACV 2018)
2017
- Cross-Platform Emoji Interpretation: Analysis, a Solution, and Applications
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Fred Morstatter, Kai Shu, Suhang Wang, and Huan Liu.
preprint in arXiv
- Attributed Signed Network Embedding
[pdf]
Suhang Wang, Charu Aggarwal, Jiliang Tang, Huan Liu
In Proceedings of 26th ACM International Conference on Information and Knowledge Management (CIKM-17)
- Randomized Feature Engineering as a Fast and Accurate Alternative to Kernel Methods
[pdf]
Suhang Wang, Charu Aggarwal, Huan Liu
In In Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data
Mining (KDD-17)
- What Your Images Reveal: Exploiting Visual Contents for Point-of-Interest Recommendation
[pdf]
Suhang Wang, Yilin Wang, Jiliang Tang, Kai Shu, Suhas Ranganath, Huan Liu
In Proceedings of the 26th World Wide Web Conference (WWW-17)
- Using a Random Forest to Inspire a Neural Network and Improving on It
[pdf][code]
Suhang Wang, Charu Aggarwal, Huan Liu
In Proceedings of the Seventeenth SIAM International Conference on Data Mining (SDM-17)
- Signed Network Embedding in Social Media
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Suhang Wang, Jiliang Tang, Charu Aggarwal, Yi Chang, Huan Liu
In Proceedings of the Seventeenth SIAM International Conference on Data Mining (SDM-17)
- Exploiting Hierarchical Structures for Unsupervised Feature Selection
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Suhang Wang, Yilin Wang, Jiliang Tang, Charu Aggarwal, Suhas Ranganath, Huan Liu
In Proceedings of the Seventeenth SIAM International Conference on Data Mining (SDM-17)
- Price Recommendation on Vacation Rental Websites
[pdf]
Yang Li, Suhang Wang, Quan Pan, Tao Yang, Jiliang Tang
In Proceedings of the Seventeenth SIAM International Conference on Data Mining (SDM-17)
- CLARE:A Joint Approach to Label Classification and Tag Recommendation
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Yilin Wang, Suhang Wang, Jiliang Tang, Guojun Qi, Huan Liu and Baoxin Li.
In Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence (AAAI-17)
2016
- Hierarchical Attention Network for Action Recognition in Videos
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Yilin Wang, Suhang Wang, Jiliang Tang, Neil O'Hare, Yi Chang and Baoxin Li.
preprint in arXiv
- Linked Document Embedding for Classifiation
[pdf]
Suhang Wang, Jiliang Tang, Charu Aggarwal, Huan Liu
In Proceedings of 25th ACM International Conference on Information and Knowledge Management (CIKM-16)
- Paired Restricted Boltzmann Machine for Linked Data
[pdf]
Suhang Wang, Jiliang Tang, Fred Morstatter, Huan Liu
In Proceedings of 25th ACM International Conference on Information and Knowledge Management (CIKM-16)
- PPP: Joint Pointwise and Pairwise Image Label Prediction
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Yilin Wang, Suhang Wang, Jiliang Tang, Huan Liu and Baoxin Li.
In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition (CVPR-16)
- Understanding and Identifying Rhetorical Questions in Social Media
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Suhas Ranganath, Xia Hu, Jiliang Tang, Suhang Wang and Huan Liu.
In Proceedings of The International AAAI Conference on Web and Social Media (ICWSM-16)
- Exploiting Emotional Information for Trust/Distrust Prediction
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Ghazaleh Beigi, Jiliang Tang, Suhang Wang and Huan Liu.
In Proceedings of SIAM International Conference on Data Mining (SDM), 2016
- Recommendation with Social Dimensions
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Jiliang Tang, Suhang Wang, Xia Hu, Dawei Yin, Yingzhou Bi, Yi Chang and Huan Liu.
In Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence (AAAI-16)
- Predicting Online Protest Participation of Social Media Users
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Suhas Ranganath, Fred Morstatter, Xia Hu, Jiliang Tang, Suhang Wang, Huan Liu
In Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence (AAAI-16)
2015
- Finding Time-Critical Responses for Information Seeking in Social Media
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Suhas Ranganath, Suhang Wang, Xia Hu, Jiliang Tang, Huan Liu
In Proceedings of IEEE International Conference on Data Mining (ICDM-15)
- Toward Dual Roles of Users in Recommender Systems
[pdf]
Suhang Wang, Jiliang Tang, Huan Liu
In Proceedings of 24th ACM International Conference on Information and Knowledge Management (CIKM-15)
- Exploring Implicit Hierarchical Structures for Recommender Systems
[pdf][code]
Suhang Wang, Jiliang Tang, Yilin Wang, Huan Liu
In Proceedings of 24th International Joint Conference on Artificial Intelligence (IJCAI-15)
- Unsupervised Sentiment Analysis for Social Media Images
[pdf]
Yilin Wang, Suhang Wang, Jiliang Tang, Huan Liu
In Proceedings of 24th International Joint Conference on Artificial Intelligence (IJCAI-15)
- Embedded Unsupervised Feature Selection
[pdf][code]
Suhang Wang, Jiliang Tang, Huan Liu
In Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI-15)
Before 2015
- Structure Preserving Low-Rank Representation for Semi-supervised Face
Recognition
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Yong Peng, Suhang Wang, Shen Wang and Bao-Liang Lu
In Proceedings of the 20th International Conference on Neural Information
Processing (ICONIP'13)
Workshop Papers
- Relevance Measurements in Online Signed Social Networks
[pdf]
Tyler Derr, Chenxing Wang, Suhang Wang and Jiliang Tang
In Proceedings of the 14TH International Workshop on Mining and Learning with Graphs (MLG-18)
- Understanding User Profiles on Social Media for Fake News Detection
[pdf]
Kai Shu, Suhang Wang, Huan Liu
In Proceedings of the 1st IEEE International Workshop on Fake MultiMedia (FakeMM-18)
- Network Embedding with Centrality Information
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Ya Ma, Suhang Wang, Jiliang Tang
In Proceedings of the IEEE International Conference on Data Mining Workshops (ICDMW-17)
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