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2020 – today
- 2025
[j27]Xijun Liang, Kaili Zhu, An Xiao, Ya Wen, Kaili Zhang, Suhang Wang, Ling Jian:
ROPU: A robust online positive-unlabeled learning algorithm. Knowl. Based Syst. 309: 112808 (2025)- [c125]Saptarshi Sengupta, Connor T. Heaton, Shreya Ghosh, Wenpeng Yin, Preslav Nakov, Suhang Wang:
TOP-Training: Target-Oriented Pretraining for Medical Extractive Question Answering. COLING 2025: 7035-7054 - [c124]Saptarshi Sengupta, Wenpeng Yin, Preslav Nakov, Shreya Ghosh, Suhang Wang:
Exploring Language Model Generalization in Low-Resource Extractive QA. COLING 2025: 7106-7126 - 2024
- [j26]Yang Li, Dongrui Wu, Suhang Wang
:
Future-generation attack and defense in neural networks. Future Gener. Comput. Syst. 152: 224 (2024) - [j25]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. Mach. Intell. Res. 21(6): 1011-1061 (2024) - [j24]Tianxiang Zhao, Xiang Zhang, Suhang Wang:
Imbalanced Node Classification With Synthetic Over-Sampling. IEEE Trans. Knowl. Data Eng. 36(12): 8515-8528 (2024) - [c123]Haitong Luo, Xuying Meng, Suhang Wang, Hanyun Cao, Weiyao Zhang, Yequan Wang, Yujun Zhang:
Spectral-Based Graph Neural Networks for Complementary Item Recommendation. AAAI 2024: 8868-8876 - [c122]Bowen Jin, Chulin Xie, Jiawei Zhang, Kashob Kumar Roy, Yu Zhang, Zheng Li, Ruirui Li, Xianfeng Tang, Suhang Wang, Yu Meng, Jiawei Han:
Graph Chain-of-Thought: Augmenting Large Language Models by Reasoning on Graphs. ACL (Findings) 2024: 163-184 - [c121]Fali Wang, Tianxiang Zhao, Junjie Xu, Suhang Wang:
HC-GST: Heterophily-aware Distribution Consistency based Graph Self-training. CIKM 2024: 2326-2335 - [c120]Junjie Xu, Enyan Dai, Dongsheng Luo, Xiang Zhang, Suhang Wang:
Shape-aware Graph Spectral Learning. CIKM 2024: 2692-2701 - [c119]Zhichao Hou, Minhua Lin, MohamadAli Torkamani, Suhang Wang, Xiaorui Liu:
Adversarial Robustness in Graph Neural Networks: Recent Advances and New Frontier. DSAA 2024: 1-2 - [c118]Xianren Zhang, Dongwon Lee, Suhang Wang:
Comprehensive Attribution: Inherently Explainable Vision Model with Feature Detector. ECCV (81) 2024: 196-213 - [c117]Fali Wang, Runxue Bao, Suhang Wang, Wenchao Yu, Yanchi Liu, Wei Cheng, Haifeng Chen:
InfuserKI: Enhancing Large Language Models with Knowledge Graphs via Infuser-Guided Knowledge Integration. EMNLP (Findings) 2024: 3675-3688 - [c116]Haoyu Wang, Ruirui Li, Zhengyang Wang, Xianfeng Tang, Danqing Zhang, Monica Xiao Cheng, Bing Yin, Jasha Droppo, Suhang Wang, Jing Gao:
LightLT: A Lightweight Representation Quantization Framework for Long-Tail Data. ICDE 2024: 1380-1393 - [c115]Tianxin Wei, Bowen Jin, Ruirui Li, Hansi Zeng, Zhengyang Wang, Jianhui Sun, Qingyu Yin, Hanqing Lu, Suhang Wang, Jingrui He, Xianfeng Tang:
Towards Unified Multi-Modal Personalization: Large Vision-Language Models for Generative Recommendation and Beyond. ICLR 2024 - [c114]Bowen Jin, Hansi Zeng, Guoyin Wang, Xiusi Chen, Tianxin Wei, Ruirui Li, Zhengyang Wang, Zheng Li, Yang Li, Hanqing Lu, Suhang Wang, Jiawei Han, Xianfeng Tang:
Language Models as Semantic Indexers. ICML 2024 - [c113]Teng Xiao, Huaisheng Zhu, Zhiwei Zhang, Zhimeng Guo, Charu C. Aggarwal, Suhang Wang, Vasant G. Honavar:
Efficient Contrastive Learning for Fast and Accurate Inference on Graphs. ICML 2024 - [c112]Zhiwei Zhang, Minhua Lin, Enyan Dai, Suhang Wang:
Rethinking Graph Backdoor Attacks: A Distribution-Preserving Perspective. KDD 2024: 4386-4397 - [c111]Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang:
Multi-source Unsupervised Domain Adaptation on Graphs with Transferability Modeling. KDD 2024: 4479-4489 - [c110]Xiaowei Qian, Zhimeng Guo, Jialiang Li, Haitao Mao, Bingheng Li, Suhang Wang, Yao Ma:
Addressing Shortcomings in Fair Graph Learning Datasets: Towards a New Benchmark. KDD 2024: 5602-5612 - [c109]Zongyu Wu, Hongcheng Gao, Yueze Wang, Xiang Zhang, Suhang Wang:
Universal Prompt Optimizer for Safe Text-to-Image Generation. NAACL-HLT 2024: 6340-6354 - [c108]Hongliang Chi, Cong Qi, Suhang Wang, Yao Ma:
Active Learning for Graphs with Noisy Structures. SDM 2024: 262-270 - [c107]Fali Wang, Runxue Bao, Suhang Wang, Wenchao Yu, Yanchi Liu, Wei Cheng, Haifeng Chen:
InfuserKI: Enhancing Large Language Models with Knowledge Graphs via Infuser-Guided Knowledge Integration. VLDB Workshops 2024 - [c106]Fali Wang, Tianxiang Zhao, Suhang Wang:
Distribution Consistency based Self-Training for Graph Neural Networks with Sparse Labels. WSDM 2024: 712-720 - [c105]Tianxiang Zhao, Wenchao Yu, Suhang Wang, Lu Wang, Xiang Zhang, Yuncong Chen, Yanchi Liu, Wei Cheng, Haifeng Chen:
Interpretable Imitation Learning with Dynamic Causal Relations. WSDM 2024: 967-975 - [c104]Bing He, Sreyashi Nag, Limeng Cui, Suhang Wang, Zheng Li, Rahul Goutam, Zhen Li, Haiyang Zhang:
Hierarchical Query Classification in E-commerce Search. WWW (Companion Volume) 2024: 338-345 - [c103]Tianxiang Zhao, Xiang Zhang, Suhang Wang:
Disambiguated Node Classification with Graph Neural Networks. WWW 2024: 914-923 - [i100]Haitong Luo, Xuying Meng, Suhang Wang, Hanyun Cao, Weiyao Zhang, Yequan Wang, Yujun Zhang:
Spectral-based Graph Neural Networks for Complementary Item Recommendation. CoRR abs/2401.02130 (2024) - [i99]Teng Xiao, Suhang Wang:
Towards Off-Policy Reinforcement Learning for Ranking Policies with Human Feedback. CoRR abs/2401.08959 (2024) - [i98]Fali Wang, Tianxiang Zhao, Suhang Wang:
Distribution Consistency based Self-Training for Graph Neural Networks with Sparse Labels. CoRR abs/2401.10394 (2024) - [i97]Hongliang Chi, Cong Qi, Suhang Wang, Yao Ma:
Active Learning for Graphs with Noisy Structures. CoRR abs/2402.02321 (2024) - [i96]Enyan Dai, Minhua Lin, Suhang Wang:
PreGIP: Watermarking the Pretraining of Graph Neural Networks for Deep Intellectual Property Protection. CoRR abs/2402.04435 (2024) - [i95]Tianxiang Zhao, Xiang Zhang, Suhang Wang:
Disambiguated Node Classification with Graph Neural Networks. CoRR abs/2402.08824 (2024) - [i94]Zongyu Wu, Hongcheng Gao, Yueze Wang, Xiang Zhang, Suhang Wang:
Universal Prompt Optimizer for Safe Text-to-Image Generation. CoRR abs/2402.10882 (2024) - [i93]Fali Wang, Runxue Bao, Suhang Wang, Wenchao Yu, Yanchi Liu, Wei Cheng, Haifeng Chen:
InfuserKI: Enhancing Large Language Models with Knowledge Graphs via Infuser-Guided Knowledge Integration. CoRR abs/2402.11441 (2024) - [i92]Qian Ma, Hongliang Chi, Hengrui Zhang, Kay Liu, Zhiwei Zhang, Lu Cheng, Suhang Wang, Philip S. Yu, Yao Ma:
Overcoming Pitfalls in Graph Contrastive Learning Evaluation: Toward Comprehensive Benchmarks. CoRR abs/2402.15680 (2024) - [i91]Xiaowei Qian, Zhimeng Guo, Jialiang Li, Haitao Mao, Bingheng Li, Suhang Wang, Yao Ma:
Addressing Shortcomings in Fair Graph Learning Datasets: Towards a New Benchmark. CoRR abs/2403.06017 (2024) - [i90]Bing He, Sreyashi Nag, Limeng Cui, Suhang Wang, Zheng Li, Rahul Goutam, Zhen Li, Haiyang Zhang:
Hierarchical Query Classification in E-commerce Search. CoRR abs/2403.06021 (2024) - [i89]Tianxin Wei, Bowen Jin, Ruirui Li, Hansi Zeng, Zhengyang Wang, Jianhui Sun, Qingyu Yin, Hanqing Lu, Suhang Wang, Jingrui He, Xianfeng Tang:
Towards Unified Multi-Modal Personalization: Large Vision-Language Models for Generative Recommendation and Beyond. CoRR abs/2403.10667 (2024) - [i88]Bowen Jin, Chulin Xie, Jiawei Zhang, Kashob Kumar Roy, Yu Zhang, Suhang Wang, Yu Meng, Jiawei Han:
Graph Chain-of-Thought: Augmenting Large Language Models by Reasoning on Graphs. CoRR abs/2404.07103 (2024) - [i87]Zhiwei Zhang, Minhua Lin, Enyan Dai, Suhang Wang:
Rethinking Graph Backdoor Attacks: A Distribution-Preserving Perspective. CoRR abs/2405.10757 (2024) - [i86]Junjie Xu, Zongyu Wu, Minhua Lin, Xiang Zhang, Suhang Wang:
LLM and GNN are Complementary: Distilling LLM for Multimodal Graph Learning. CoRR abs/2406.01032 (2024) - [i85]Zhiwei Zhang, Minhua Lin, Junjie Xu, Zongyu Wu, Enyan Dai, Suhang Wang:
Robustness-Inspired Defense Against Backdoor Attacks on Graph Neural Networks. CoRR abs/2406.09836 (2024) - [i84]Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang:
Multi-source Unsupervised Domain Adaptation on Graphs with Transferability Modeling. CoRR abs/2406.10425 (2024) - [i83]Quan Li, Tianxiang Zhao, Lingwei Chen, Junjie Xu, Suhang Wang:
Enhancing Data-Limited Graph Neural Networks by Actively Distilling Knowledge from Large Language Models. CoRR abs/2407.13989 (2024) - [i82]Fali Wang, Tianxiang Zhao, Junjie Xu, Suhang Wang:
HC-GST: Heterophily-aware Distribution Consistency based Graph Self-training. CoRR abs/2407.17787 (2024) - [i81]Xianren Zhang, Dongwon Lee, Suhang Wang:
Comprehensive Attribution: Inherently Explainable Vision Model with Feature Detector. CoRR abs/2407.19308 (2024) - [i80]Saptarshi Sengupta, Wenpeng Yin, Preslav Nakov, Shreya Ghosh, Suhang Wang:
Exploring Language Model Generalization in Low-Resource Extractive QA. CoRR abs/2409.18446 (2024) - [i79]Haitong Luo, Xuying Meng, Suhang Wang, Tianxiang Zhao, Fali Wang, Hanyun Cao, Yujun Zhang:
Enhance Graph Alignment for Large Language Models. CoRR abs/2410.11370 (2024) - [i78]Xianren Zhang, Xianfeng Tang, Hui Liu, Zongyu Wu, Qi He, Dongwon Lee, Suhang Wang:
Divide-Verify-Refine: Aligning LLM Responses with Complex Instructions. CoRR abs/2410.12207 (2024) - [i77]Minhua Lin, Zhiwei Zhang, Enyan Dai, Zongyu Wu, Yilong Wang, Xiang Zhang, Suhang Wang:
Trojan Prompt Attacks on Graph Neural Networks. CoRR abs/2410.13974 (2024) - [i76]Zhiwei Zhang, Fali Wang, Xiaomin Li, Zongyu Wu, Xianfeng Tang, Hui Liu, Qi He, Wenpeng Yin, Suhang Wang:
Does your LLM truly unlearn? An embarrassingly simple approach to recover unlearned knowledge. CoRR abs/2410.16454 (2024) - [i75]Minhua Lin, Zhengzhang Chen, Yanchi Liu, Xujiang Zhao, Zongyu Wu, Junxiang Wang, Xiang Zhang, Suhang Wang, Haifeng Chen:
Decoding Time Series with LLMs: A Multi-Agent Framework for Cross-Domain Annotation. CoRR abs/2410.17462 (2024) - [i74]Fali Wang, Zhiwei Zhang, Xianren Zhang, Zongyu Wu, Tzuhao Mo, Qiuhao Lu, Wanjing Wang, Rui Li, Junjie Xu, Xianfeng Tang, Qi He, Yao Ma, Ming Huang, Suhang Wang:
A Comprehensive Survey of Small Language Models in the Era of Large Language Models: Techniques, Enhancements, Applications, Collaboration with LLMs, and Trustworthiness. CoRR abs/2411.03350 (2024) - [i73]Juanhui Li, Sreyashi Nag, Hui Liu, Xianfeng Tang, Sheikh Sarwar, Limeng Cui, Hansu Gu, Suhang Wang, Qi He, Jiliang Tang:
Learning with Less: Knowledge Distillation from Large Language Models via Unlabeled Data. CoRR abs/2411.08028 (2024) - [i72]Minhua Lin, Enyan Dai, Junjie Xu, Jinyuan Jia, Xiang Zhang, Suhang Wang:
Stealing Training Graphs from Graph Neural Networks. CoRR abs/2411.11197 (2024) - [i71]Liangru Xie, Hui Liu, Jingying Zeng, Xianfeng Tang, Yan Han, Chen Luo, Jing Huang, Zhen Li, Suhang Wang, Qi He:
A Survey of Calibration Process for Black-Box LLMs. CoRR abs/2412.12767 (2024) - 2023
- [j23]Huaisheng Zhu, Enyan Dai, Hui Liu, Suhang Wang:
Learning fair models without sensitive attributes: A generative approach. Neurocomputing 561: 126841 (2023) - [j22]Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang:
Faithful and Consistent Graph Neural Network Explanations with Rationale Alignment. ACM Trans. Intell. Syst. Technol. 14(5): 92:1-92:23 (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) - [c102]Zhimeng Guo, Jialiang Li, Teng Xiao, Yao Ma, Suhang Wang:
Towards Fair Graph Neural Networks via Graph Counterfactual. CIKM 2023: 669-678 - [c101]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 - [c100]Yitang Wang, Suhang Wang, Yong Pang, Xueguan Song:
Outlier Detection and Correction for Time Series Data of Tunnel Boring Machine. ICIRA (6) 2023: 254-261 - [c99]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 - [c98]Teng Xiao, Zhengyu Chen, Suhang Wang:
Reconsidering Learning Objectives in Unbiased Recommendation: A Distribution Shift Perspective. KDD 2023: 2764-2775 - [c97]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 - [c96]Yu Wang, Zhengyang Wang, Hengrui Zhang, Qingyu Yin, Xianfeng Tang, Yinghan Wang, Danqing Zhang, Limeng Cui, Monica Xiao Cheng, Bing Yin, Suhang Wang, Philip S. Yu:
Exploiting Intent Evolution in E-commercial Query Recommendation. KDD 2023: 5162-5173 - [c95]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. NeurIPS 2023 - [c94]Minhua Lin, Teng Xiao, Enyan Dai, Xiang Zhang, Suhang Wang:
Certifiably Robust Graph Contrastive Learning. NeurIPS 2023 - [c93]Teng Xiao, Huaisheng Zhu, Zhengyu Chen, Suhang Wang:
Simple and Asymmetric Graph Contrastive Learning without Augmentations. NeurIPS 2023 - [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 - [i70]Tianxiang Zhao, Dongsheng Luo, Xiang Zhang, Suhang Wang:
Faithful and Consistent Graph Neural Network Explanations with Rationale Alignment. CoRR abs/2301.02791 (2023) - [i69]Enyan Dai, Minhua Lin, Xiang Zhang, Suhang Wang:
Unnoticeable Backdoor Attacks on Graph Neural Networks. CoRR abs/2303.01263 (2023) - [i68]Zhimeng Guo, Teng Xiao, Charu Aggarwal, Hui Liu, Suhang Wang:
Counterfactual Learning on Graphs: A Survey. CoRR abs/2304.01391 (2023) - [i67]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) - [i66]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) - [i65]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) - [i64]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) - [i63]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) - [i62]Yang Li, Kangbo Liu, Ranjan Satapathy, Suhang Wang, Erik Cambria:
Recent Developments in Recommender Systems: A Survey. CoRR abs/2306.12680 (2023) - [i61]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) - [i60]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) - [i59]Tianxiang Zhao, Wenchao Yu, Suhang Wang, Lu Wang, Xiang Zhang, Yuncong Chen, Yanchi Liu, Wei Cheng, Haifeng Chen:
Dynamic DAG Discovery for Interpretable Imitation Learning. CoRR abs/2310.00489 (2023) - [i58]Teng Xiao, Zhengyu Chen, Donglin Wang, Suhang Wang:
Learning How to Propagate Messages in Graph Neural Networks. CoRR abs/2310.00697 (2023) - [i57]Minhua Lin, Teng Xiao, Enyan Dai, Xiang Zhang, Suhang Wang:
Certifiably Robust Graph Contrastive Learning. CoRR abs/2310.03312 (2023) - [i56]Bowen Jin, Hansi Zeng, Guoyin Wang, Xiusi Chen, Tianxin Wei, Ruirui Li, Zhengyang Wang, Zheng Li, Yang Li, Hanqing Lu, Suhang Wang, Jiawei Han, Xianfeng Tang:
Language Models As Semantic Indexers. CoRR abs/2310.07815 (2023) - [i55]Junjie Xu, Enyan Dai, Dongsheng Luo, Xiang Zhang, Suhang Wang:
Learning Graph Filters for Spectral GNNs via Newton Interpolation. CoRR abs/2310.10064 (2023) - [i54]Teng Xiao, Huaisheng Zhu, Zhengyu Chen, Suhang Wang:
Simple and Asymmetric Graph Contrastive Learning without Augmentations. CoRR abs/2310.18884 (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]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, Charu C. Aggarwal, Suhas Ranganath, Huan Liu:
Exploiting Hierarchical Structures for Unsupervised Feature Selection. SDM 2017: 507-515 - [c14]Suhang Wang, Yilin Wang, Jiliang Tang, Kai Shu, Suhas Ranganath, Huan Liu:
What Your Images Reveal: Exploiting Visual Contents for Point-of-Interest Recommendation. WWW 2017: 391-400 - [r1]Suhang Wang, Jiliang Tang, Huan Liu:
Feature Selection. Encyclopedia of Machine Learning and Data Mining 2017: 503-511 - [i8]Kai Shu, Amy Sliva, Suhang Wang, Jiliang Tang, Huan Liu:
Fake News Detection on Social Media: A Data Mining Perspective. CoRR abs/1708.01967 (2017) - [i7]Fred Morstatter, Kai Shu, Suhang Wang, Huan Liu:
Cross-Platform Emoji Interpretation: Analysis, a Solution, and Applications. CoRR abs/1709.04969 (2017) - [i6]Yang Li, Quan Pan, Suhang Wang, Haiyun Peng, Tao Yang, Erik Cambria:
Disentangled Variational Auto-Encoder for Semi-supervised Learning. CoRR abs/1709.05047 (2017) - [i5]Tyler Derr, Chenxing Wang, Suhang Wang, Jiliang Tang:
Signed Node Relevance Measurements. CoRR abs/1710.07236 (2017) - [i4]Yao Ma, Suhang Wang, Zhaochun Ren, Dawei Yin, Jiliang Tang:
Preserving Local and Global Information for Network Embedding. CoRR abs/1710.07266 (2017) - [i3]Kai Shu, Suhang Wang, Huan Liu:
Exploiting Tri-Relationship for Fake News Detection. CoRR abs/1712.07709 (2017) - 2016
- [j3]Kai Shu, Suhang Wang, Jiliang Tang, Reza Zafarani, Huan Liu:
User Identity Linkage across Online Social Networks: A Review. SIGKDD Explor. 18(2): 5-17 (2016) - [c13]Suhas Ranganath, Fred Morstatter, Xia Hu, Jiliang Tang, Suhang Wang, Huan Liu:
Predicting Online Protest Participation of Social Media Users. AAAI 2016: 208-214 - [c12]Jiliang Tang, Suhang Wang, Xia Hu, Dawei Yin, Yingzhou Bi, Yi Chang, Huan Liu:
Recommendation with Social Dimensions. AAAI 2016: 251-257 - [c11]Suhang Wang, Jiliang Tang, Charu C. Aggarwal, Huan Liu:
Linked Document Embedding for Classification. CIKM 2016: 115-124 - [c10]Suhang Wang, Jiliang Tang, Fred Morstatter, Huan Liu:
Paired Restricted Boltzmann Machine for Linked Data. CIKM 2016: 1753-1762 - [c9]Yilin Wang, Suhang Wang, Jiliang Tang, Huan Liu, Baoxin Li:
PPP: Joint Pointwise and Pairwise Image Label Prediction. CVPR 2016: 6005-6013 - [c8]Suhas Ranganath, Xia Hu, Jiliang Tang, Suhang Wang, Huan Liu:
Identifying Rhetorical Questions in Social Media. ICWSM 2016: 667-670 - [c7]Ghazaleh Beigi, Jiliang Tang, Suhang Wang, Huan Liu:
Exploiting Emotional Information for Trust/Distrust Prediction. SDM 2016: 81-89 - [i2]Jundong Li, Kewei Cheng, Suhang Wang, Fred Morstatter, Robert P. Trevino, Jiliang Tang, Huan Liu:
Feature Selection: A Data Perspective. CoRR abs/1601.07996 (2016) - [i1]Yilin Wang, Suhang Wang, Jiliang Tang, Neil O'Hare, Yi Chang, Baoxin Li:
Hierarchical Attention Network for Action Recognition in Videos. CoRR abs/1607.06416 (2016) - 2015
- [j2]Yong Peng, Suhang Wang, Xianzhong Long, Bao-Liang Lu:
Discriminative graph regularized extreme learning machine and its application to face recognition. Neurocomputing 149: 340-353 (2015) - [j1]Yong Peng, Bao-Liang Lu, Suhang Wang:
Enhanced low-rank representation via sparse manifold adaption for semi-supervised learning. Neural Networks 65: 1-17 (2015) - [c6]Suhang Wang, Jiliang Tang, Huan Liu:
Embedded Unsupervised Feature Selection. AAAI 2015: 470-476 - [c5]Suhang Wang, Jiliang Tang, Huan Liu:
Toward Dual Roles of Users in Recommender Systems. CIKM 2015: 1651-1660 - [c4]Suhas Ranganath, Suhang Wang, Xia Hu, Jiliang Tang, Huan Liu:
Finding Time-Critical Responses for Information Seeking in Social Media. ICDM 2015: 961-966 - [c3]Suhang Wang, Jiliang Tang, Yilin Wang, Huan Liu:
Exploring Implicit Hierarchical Structures for Recommender Systems. IJCAI 2015: 1813-1819 - [c2]Yilin Wang, Suhang Wang, Jiliang Tang, Huan Liu, Baoxin Li:
Unsupervised Sentiment Analysis for Social Media Images. IJCAI 2015: 2378-2379 - 2013
- [c1]Yong Peng, Suhang Wang, Shen Wang, Bao-Liang Lu:
Structure Preserving Low-Rank Representation for Semi-supervised Face Recognition. ICONIP (2) 2013: 148-155
Coauthor Index
[j20] [j16] [c62] [c59] [c51] [i30] [j12] [c47] [c45] [c44] [c41] [c40] [c37] [c34] [c33] [i21] [i19] [i17] [j11] [j9] [j8] [j7] [c32] [c31] [c30] [c28] [c26] [c25] [c23] [i9] [j5] [j4] [c22] [c21] [c19] [c18] [c17] [c15] [c14] [r1] [i8] [i7] [i3] [j3] [c13] [c12] [c11] [c10] [c9] [c8] [c7] [i2] [c6] [c5] [c4] [c3] [c2]
[j25] [i73] [c101] [c95] [i60] [i50] [c73] [i33] [c64] [c60] [c57] [c52] [i28] [i26] [i25] [c36] [c35] [i20] [i18] [j11] [j9] [j7] [c30] [c29] [c24] [c23] [i10] [j6] [j5] [j4] [c22] [c21] [c20] [c17] [c16] [c15] [c14] [r1] [i8] [i5] [i4] [j3] [c13] [c12] [c11] [c10] [c9] [c8] [c7] [i2] [i1] [c6] [c5] [c4] [c3] [c2]
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the dblp computer science bibliography is funded and supported by:
