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ORCIDYao Ma 0001
Person information
- affiliation: Rensselaer Polytechnic Institute, Troy, NY, USA
- affiliation (2021 - 2023): New Jersey Institute of Technology, Newark, NJ, USA
- affiliation (PhD 2021): Michigan State University, East Lansing, MI, USA
Other persons with the same name
- Yao Ma — disambiguation page
- Yao Ma 0002
![[0000-0001-6451-8720]](https://dblp.dagstuhl.de/img/orcid-mark.12x12.png "0000-0001-6451-8720")
— Texas Tech University, Lubbock, TX, USA (and 1 more) - Yao Ma 0004 — National Institute of Standards and Technology, Boulder, CO, USA (and 5 more)
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2020 – today
- 2025
[j9]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. ACM Trans. Intell. Syst. Technol. 16(6): 145:1-145:87 (2025)- [j8]Hongjia Xu, Liangliang Zhang, Yao Ma, Sheng Zhou, Zhuonan Zheng, Jiajun Bu:
Learning to Reduce the Scale of Large Graphs: A Comprehensive Survey. ACM Trans. Knowl. Discov. Data 19(5): 1-25 (2025) - [j7]Liangliang Zhang, Haoran Bao, Yao Ma:
Extending Graph Condensation to Multi-Label Datasets: A Benchmark Study. Trans. Mach. Learn. Res. 2025 (2025) - [j6]Yuanchen Bei, Sheng Zhou, Jinke Shi, Yao Ma, Haishuai Wang, Jiajun Bu:
Guarding Graph Neural Networks for Unsupervised Graph Anomaly Detection. IEEE Trans. Neural Networks Learn. Syst. 36(9): 16840-16853 (2025) - [c57]Pritam Sen, Yao Ma, Cristian Borcea:
CryptGNN: Enabling Secure Inference for Graph Neural Networks. CCS 2025: 291-305 - [c56]Hongliang Chi, Wei Jin, Charu C. Aggarwal, Yao Ma:
Precedence-Constrained Winter Value for Effective Graph Data Valuation. ICLR 2025 - [c55]Hongliang Chi, Qiong Wu, Zhengyi Zhou, Yao Ma:
Shapley-Guided Utility Learning for Effective Graph Inference Data Valuation. ICLR 2025 - [c54]Fali Wang, Minhua Lin, Yao Ma, Hui Liu, Qi He, Xianfeng Tang, Jiliang Tang, Jian Pei, Suhang Wang:
A Survey on Small Language Models in the Era of Large Language Models: Architecture, Capabilities, and Trustworthiness. KDD (2) 2025: 6173-6183 - [c53]Haitao Mao, Guangliang Liu, Yao Ma, Rongrong Wang, Kristen Marie Johnson, Jiliang Tang:
A Survey to Recent Progress Towards Understanding In-Context Learning. NAACL (Findings) 2025: 7302-7323 - [i57]Hongliang Chi, Qiong Wu, Zhengyi Zhou, Jonathan Light, Emily Dodwell, Yao Ma:
Unifying and Optimizing Data Values for Selection via Sequential-Decision-Making. CoRR abs/2502.04554 (2025) - [i56]Yuxiang Wang, Xinnan Dai, Wenqi Fan, Yao Ma:
Exploring Graph Tasks with Pure LLMs: A Comprehensive Benchmark and Investigation. CoRR abs/2502.18771 (2025) - [i55]Yuxiang Wang, Wenqi Fan, Suhang Wang, Yao Ma:
Towards Graph Foundation Models: A Transferability Perspective. CoRR abs/2503.09363 (2025) - [i54]Hongliang Chi, Qiong Wu, Zhengyi Zhou, Yao Ma:
Shapley-Guided Utility Learning for Effective Graph Inference Data Valuation. CoRR abs/2503.18195 (2025) - [i53]Utkarsh Sahu, Zhisheng Qi, Yongjia Lei, Ryan A. Rossi, Franck Dernoncourt, Nesreen K. Ahmed, Mahantesh M. Halappanavar, Yao Ma, Yu Wang:
A Graph Perspective to Probe Structural Patterns of Knowledge in Large Language Models. CoRR abs/2505.19286 (2025) - [i52]Liangliang Zhang, Zhuorui Jiang, Hongliang Chi, Haoyang Chen, Mohammed Elkoumy, Fali Wang, Qiong Wu, Zhengyi Zhou, Shirui Pan, Suhang Wang, Yao Ma:
Diagnosing and Addressing Pitfalls in KG-RAG Datasets: Toward More Reliable Benchmarking. CoRR abs/2505.23495 (2025) - [i51]Utkarsh Sahu, Zhisheng Qi, Mahantesh Halappanavar, Nedim Lipka, Ryan A. Rossi, Franck Dernoncourt, Yu Zhang, Yao Ma, Yu Wang:
Knowledge Homophily in Large Language Models. CoRR abs/2509.23773 (2025) - 2024
- [c52]Haitao Mao, Juanhui Li, Harry Shomer, Bingheng Li, Wenqi Fan, Yao Ma, Tong Zhao, Neil Shah, Jiliang Tang:
Revisiting Link Prediction: a data perspective. ICLR 2024 - [c51]Bingheng Li, Linxin Yang, Yupeng Chen, Senmiao Wang, Haitao Mao, Qian Chen, Yao Ma, Akang Wang, Tian Ding, Jiliang Tang, Ruoyu Sun:
PDHG-Unrolled Learning-to-Optimize Method for Large-Scale Linear Programming. ICML 2024 - [c50]Haitao Mao, Zhikai Chen, Wenzhuo Tang, Jianan Zhao, Yao Ma, Tong Zhao, Neil Shah, Mikhail Galkin, Jiliang Tang:
Position: Graph Foundation Models Are Already Here. ICML 2024 - [c49]Hongliang Chi, Yao Ma:
Enhancing Contrastive Learning on Graphs with Node Similarity. KDD 2024: 456-465 - [c48]Harry Shomer, Yao Ma, Haitao Mao, Juanhui Li, Bo Wu, Jiliang Tang:
LPFormer: An Adaptive Graph Transformer for Link Prediction. KDD 2024: 2686-2698 - [c47]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 - [c46]Tianyi Zhao, Liangliang Zhang, Yao Ma, Lu Cheng:
A Survey on Safe Multi-Modal Learning Systems. KDD 2024: 6655-6665 - [c45]Qian Ma, Haitao Mao, Jingzhe Liu, Zhehua Zhang, Chunlin Feng, Yu Song, Yihan Shao, Yao Ma:
Do Neural Scaling Laws Exist on Graph Self-Supervised Learning? LoG 2024: 35 - [c44]Hongliang Chi, Cong Qi, Suhang Wang, Yao Ma:
Active Learning for Graphs with Noisy Structures. SDM 2024: 262-270 - [c43]Mahmoud Nazzal, Issa Khalil, Abdallah Khreishah, NhatHai Phan, Yao Ma:
Multi-Instance Adversarial Attack on GNN-Based Malicious Domain Detection. SP 2024: 1236-1254 - [c42]Inwon Kang, Maruf Ahmed Mridul, Abraham Sanders, Yao Ma, Thilanka Munasinghe, Aparna Gupta, Oshani Seneviratne:
Deciphering Crypto Twitter. WebSci 2024: 331-342 - [c41]Tyler Derr, Yao Ma, Kaize Ding, Tong Zhao, Nesreen K. Ahmed:
The 5th International Workshop on Machine Learning on Graphs (MLoG). WSDM 2024: 1210-1211 - [c40]Wei Jin, Haohan Wang, Daochen Zha, Qiaoyu Tan, Yao Ma, Sharon Li, Su-In Lee:
DCAI: Data-centric Artificial Intelligence. WWW (Companion Volume) 2024: 1482-1485 - [c39]Lin Wang, Wenqi Fan, Jiatong Li, Yao Ma, Qing Li:
Fast Graph Condensation with Structure-based Neural Tangent Kernel. WWW 2024: 4439-4448 - [i50]Hongliang Chi, Wei Jin, Charu Aggarwal, Yao Ma:
Precedence-Constrained Winter Value for Effective Graph Data Valuation. CoRR abs/2402.01943 (2024) - [i49]Hongjia Xu, Liangliang Zhang, Yao Ma, Sheng Zhou, Zhuonan Zheng, Jiajun Bu:
A Survey on Graph Condensation. CoRR abs/2402.02000 (2024) - [i48]Haitao Mao, Guangliang Liu, Yao Ma, Rongrong Wang, Jiliang Tang:
A Data Generation Perspective to the Mechanism of In-Context Learning. CoRR abs/2402.02212 (2024) - [i47]Haitao Mao, Zhikai Chen, Wenzhuo Tang, Jianan Zhao, Yao Ma, Tong Zhao, Neil Shah, Mikhail Galkin, Jiliang Tang:
Graph Foundation Models. CoRR abs/2402.02216 (2024) - [i46]Hongliang Chi, Cong Qi, Suhang Wang, Yao Ma:
Active Learning for Graphs with Noisy Structures. CoRR abs/2402.02321 (2024) - [i45]Tianyi Zhao, Liangliang Zhang, Yao Ma, Lu Cheng:
A Survey on Safe Multi-Modal Learning System. CoRR abs/2402.05355 (2024) - [i44]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) - [i43]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) - [i42]Inwon Kang, Maruf Ahmed Mridul, Abraham Sanders, Yao Ma, Thilanka Munasinghe, Aparna Gupta, Oshani Seneviratne:
Deciphering Crypto Twitter. CoRR abs/2403.06036 (2024) - [i41]Yuanchen Bei, Sheng Zhou, Jinke Shi, Yao Ma, Haishuai Wang, Jiajun Bu:
Guarding Graph Neural Networks for Unsupervised Graph Anomaly Detection. CoRR abs/2404.16366 (2024) - [i40]Zhuonan Zheng, Yuanchen Bei, Sheng Zhou, Yao Ma, Ming Gu, Hongjia Xu, Chengyu Lai, Jiawei Chen, Jiajun Bu:
Revisiting the Message Passing in Heterophilous Graph Neural Networks. CoRR abs/2405.17768 (2024) - [i39]Bingheng Li, Linxin Yang, Yupeng Chen, Senmiao Wang, Qian Chen, Haitao Mao, Yao Ma, Akang Wang, Tian Ding, Jiliang Tang, Ruoyu Sun:
PDHG-Unrolled Learning-to-Optimize Method for Large-Scale Linear Programming. CoRR abs/2406.01908 (2024) - [i38]Qian Ma, Haitao Mao, Jingzhe Liu, Zhehua Zhang, Chunlin Feng, Yu Song, Yihan Shao, Yao Ma:
Do Neural Scaling Laws Exist on Graph Self-Supervised Learning? CoRR abs/2408.11243 (2024) - [i37]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) - [i36]Liangliang Zhang, Haoran Bao, Yao Ma:
Extending Graph Condensation to Multi-Label Datasets: A Benchmark Study. CoRR abs/2412.17961 (2024) - 2023
- [j5]Yiqi Wang, Yao Ma, Wei Jin, Chaozhuo Li, Charu Aggarwal, Jiliang Tang:
Customized Graph Nerual Networks. IEEE Data Eng. Bull. 47(2): 108-125 (2023) - [j4]Wenqi Fan, Xiangyu Zhao, Qing Li, Tyler Derr, Yao Ma, Hui Liu, Jianping Wang, Jiliang Tang:
Adversarial Attacks for Black-Box Recommender Systems via Copying Transferable Cross-Domain User Profiles. IEEE Trans. Knowl. Data Eng. 35(12): 12415-12429 (2023) - [c38]Juanhui Li, Harry Shomer, Jiayuan Ding, Yiqi Wang, Yao Ma, Neil Shah, Jiliang Tang, Dawei Yin:
Are Message Passing Neural Networks Really Helpful for Knowledge Graph Completion? ACL (1) 2023: 10696-10711 - [c37]Harry Shomer, Wei Jin, Juanhui Li, Yao Ma, Hui Liu:
Learning Representations for Hyper-Relational Knowledge Graphs. ASONAM 2023: 253-257 - [c36]Zhimeng Guo, Jialiang Li, Teng Xiao, Yao Ma, Suhang Wang:
Towards Fair Graph Neural Networks via Graph Counterfactual. CIKM 2023: 669-678 - [c35]Harry Shomer, Yao Ma, Juanhui Li, Bo Wu, Charu C. Aggarwal, Jiliang Tang:
Distance-Based Propagation for Efficient Knowledge Graph Reasoning. EMNLP 2023: 14692-14707 - [c34]Juanhui Li, Harry Shomer, Haitao Mao, Shenglai Zeng, Yao Ma, Neil Shah, Jiliang Tang, Dawei Yin:
Evaluating Graph Neural Networks for Link Prediction: Current Pitfalls and New Benchmarking. NeurIPS 2023 - [c33]Haitao Mao, Zhikai Chen, Wei Jin, Haoyu Han, Yao Ma, Tong Zhao, Neil Shah, Jiliang Tang:
Demystifying Structural Disparity in Graph Neural Networks: Can One Size Fit All? NeurIPS 2023 - [c32]Juanhui Li, Wei Zeng, Suqi Cheng, Yao Ma, Jiliang Tang, Shuaiqiang Wang, Dawei Yin:
Graph Enhanced BERT for Query Understanding. SIGIR 2023: 3315-3319 - [c31]Tyler Derr, Yao Ma, Benedek Rozemberczki, Neil Shah, Shirui Pan:
The 3rd International Workshop on Machine Learning on Graphs (MLoG). WSDM 2023: 1271-1272 - [i35]Haitao Mao, Zhikai Chen, Wei Jin, Haoyu Han, Yao Ma, Tong Zhao, Neil Shah, Jiliang Tang:
Demystifying Structural Disparity in Graph Neural Networks: Can One Size Fit All? CoRR abs/2306.01323 (2023) - [i34]Juanhui Li, Harry Shomer, Haitao Mao, Shenglai Zeng, Yao Ma, Neil Shah, Jiliang Tang, Dawei Yin:
Evaluating Graph Neural Networks for Link Prediction: Current Pitfalls and New Benchmarking. CoRR abs/2306.10453 (2023) - [i33]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) - [i32]Mahmoud Nazzal, Issa Khalil, Abdallah Khreishah, NhatHai Phan, Yao Ma:
Multi-Instance Adversarial Attack on GNN-Based Malicious Domain Detection. CoRR abs/2308.11754 (2023) - [i31]Haitao Mao, Juanhui Li, Harry Shomer, Bingheng Li, Wenqi Fan, Yao Ma, Tong Zhao, Neil Shah, Jiliang Tang:
Revisiting Link Prediction: A Data Perspective. CoRR abs/2310.00793 (2023) - [i30]Harry Shomer, Yao Ma, Haitao Mao, Juanhui Li, Bo Wu, Jiliang Tang:
Adaptive Pairwise Encodings for Link Prediction. CoRR abs/2310.11009 (2023) - [i29]Lin Wang, Wenqi Fan, Jiatong Li, Yao Ma, Qing Li:
Fast Graph Condensation with Structure-based Neural Tangent Kernel. CoRR abs/2310.11046 (2023) - [i28]Harry Shomer, Yao Ma, Juanhui Li, Bo Wu, Charu C. Aggarwal, Jiliang Tang:
Distance-Based Propagation for Efficient Knowledge Graph Reasoning. CoRR abs/2311.01024 (2023) - 2022
- [j3]Rui Miao, Yintao Yang, Yao Ma, Xin Juan, Haotian Xue, Jiliang Tang, Ying Wang, Xin Wang:
Negative samples selecting strategy for graph contrastive learning. Inf. Sci. 613: 667-681 (2022) - [j2]Wenqi Fan, Yao Ma, Qing Li, Jianping Wang, Guoyong Cai, Jiliang Tang, Dawei Yin:
A Graph Neural Network Framework for Social Recommendations. IEEE Trans. Knowl. Data Eng. 34(5): 2033-2047 (2022) - [c30]Khang Tran, Phung Lai, NhatHai Phan, Issa Khalil, Yao Ma, Abdallah Khreishah, My T. Thai, Xintao Wu:
Heterogeneous Randomized Response for Differential Privacy in Graph Neural Networks. IEEE Big Data 2022: 1582-1587 - [c29]Yufei He, Yao Ma:
SGKD: A Scalable and Effective Knowledge Distillation Framework for Graph Representation Learning. ICDM (Workshops) 2022: 666-673 - [c28]Yao Ma, Xiaorui Liu, Neil Shah, Jiliang Tang:
Is Homophily a Necessity for Graph Neural Networks? ICLR 2022 - [c27]Wei Jin, Xiaorui Liu, Xiangyu Zhao, Yao Ma, Neil Shah, Jiliang Tang:
Automated Self-Supervised Learning for Graphs. ICLR 2022 - [c26]Wei Jin, Xiaorui Liu, Yao Ma, Charu C. Aggarwal, Jiliang Tang:
Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective. KDD 2022: 709-719 - [i27]Juan-Hui Li, Yao Ma, Wei Zeng, Suqi Cheng, Jiliang Tang, Shuaiqiang Wang, Dawei Yin:
Graph Enhanced BERT for Query Understanding. CoRR abs/2204.06522 (2022) - [i26]Juan-Hui Li, Harry Shomer, Jiayuan Ding, Yiqi Wang, Yao Ma, Neil Shah, Jiliang Tang, Dawei Yin:
Are Graph Neural Networks Really Helpful for Knowledge Graph Completion? CoRR abs/2205.10652 (2022) - [i25]Wei Jin, Xiaorui Liu, Yao Ma, Charu C. Aggarwal, Jiliang Tang:
Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective. CoRR abs/2206.07743 (2022) - [i24]Hongliang Chi, Yao Ma:
Enhancing Graph Contrastive Learning with Node Similarity. CoRR abs/2208.06743 (2022) - [i23]Harry Shomer, Wei Jin, Juan-Hui Li, Yao Ma, Jiliang Tang:
Learning Representations for Hyper-Relational Knowledge Graphs. CoRR abs/2208.14322 (2022) - [i22]Khang Tran, Phung Lai, NhatHai Phan, Issa Khalil, Yao Ma, Abdallah Khreishah, My Tra Thai, Xintao Wu:
Heterogeneous Randomized Response for Differential Privacy in Graph Neural Networks. CoRR abs/2211.05766 (2022) - 2021
- [c25]Wei Jin, Xiaorui Liu, Yao Ma, Tyler Derr, Charu C. Aggarwal, Jiliang Tang:
Graph Feature Gating Networks. CIKM 2021: 813-822 - [c24]Yao Ma, Xiaorui Liu, Tong Zhao, Yozen Liu, Jiliang Tang, Neil Shah:
A Unified View on Graph Neural Networks as Graph Signal Denoising. CIKM 2021: 1202-1211 - [c23]Wenqi Fan, Tyler Derr, Xiangyu Zhao, Yao Ma, Hui Liu, Jianping Wang, Jiliang Tang, Qing Li:
Attacking Black-box Recommendations via Copying Cross-domain User Profiles. ICDE 2021: 1583-1594 - [c22]Xiaorui Liu, Wei Jin, Yao Ma, Yaxin Li, Hua Liu, Yiqi Wang, Ming Yan, Jiliang Tang:
Elastic Graph Neural Networks. ICML 2021: 6837-6849 - [c21]Yao Ma, Suhang Wang, Tyler Derr, Lingfei Wu, Jiliang Tang:
Graph Adversarial Attack via Rewiring. KDD 2021: 1161-1169 - [c20]Wei Jin, Yao Ma, Yiqi Wang, Xiaorui Liu, Jiliang Tang, Yukuo Cen, Jiezhong Qiu, Jie Tang, Chuan Shi, Yanfang Ye, Jiawei Zhang, Philip S. Yu:
Graph Representation Learning: Foundations, Methods, Applications and Systems. KDD 2021: 4044-4045 - [c19]Xiaorui Liu, Jiayuan Ding, Wei Jin, Han Xu, Yao Ma, Zitao Liu, Jiliang Tang:
Graph Neural Networks with Adaptive Residual. NeurIPS 2021: 9720-9733 - [c18]Wei Jin, Tyler Derr, Yiqi Wang, Yao Ma, Zitao Liu, Jiliang Tang:
Node Similarity Preserving Graph Convolutional Networks. WSDM 2021: 148-156 - [i21]Wei Jin, Xiaorui Liu, Yao Ma, Tyler Derr, Charu C. Aggarwal, Jiliang Tang:
Graph Feature Gating Networks. CoRR abs/2105.04493 (2021) - [i20]Wei Jin, Xiaorui Liu, Xiangyu Zhao, Yao Ma, Neil Shah, Jiliang Tang:
Automated Self-Supervised Learning for Graphs. CoRR abs/2106.05470 (2021) - [i19]Yao Ma, Xiaorui Liu, Neil Shah, Jiliang Tang:
Is Homophily a Necessity for Graph Neural Networks? CoRR abs/2106.06134 (2021) - [i18]Xiaorui Liu, Wei Jin, Yao Ma, Yaxin Li, Hua Liu, Yiqi Wang, Ming Yan, Jiliang Tang:
Elastic Graph Neural Networks. CoRR abs/2107.06996 (2021) - 2020
- [j1]Han Xu, Yao Ma, Haochen Liu, Debayan Deb, Hui Liu, Jiliang Tang, Anil K. Jain:
Adversarial Attacks and Defenses in Images, Graphs and Text: A Review. Int. J. Autom. Comput. 17(2): 151-178 (2020) - [c17]Juan-Hui Li, Yao Ma, Yiqi Wang, Charu C. Aggarwal, Chang-Dong Wang, Jiliang Tang:
Graph Pooling with Representativeness. ICDM 2020: 302-311 - [c16]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 - [c15]Wei Jin, Yao Ma, Xiaorui Liu, Xianfeng Tang, Suhang Wang, Jiliang Tang:
Graph Structure Learning for Robust Graph Neural Networks. KDD 2020: 66-74 - [c14]Yu Rong, Tingyang Xu, Junzhou Huang, Wenbing Huang, Hong Cheng, Yao Ma, Yiqi Wang, Tyler Derr, Lingfei Wu, Tengfei Ma:
Deep Graph Learning: Foundations, Advances and Applications. KDD 2020: 3555-3556 - [c13]Wenqi Fan, Yao Ma, Han Xu, Xiaorui Liu, Jianping Wang, Qing Li, Jiliang Tang:
Deep Adversarial Canonical Correlation Analysis. SDM 2020: 352-360 - [c12]Yao Ma, Ziyi Guo, Zhaochun Ren, Jiliang Tang, Dawei Yin:
Streaming Graph Neural Networks. SIGIR 2020: 719-728 - [c11]Tyler Derr, Yao Ma, Wenqi Fan, Xiaorui Liu, Charu C. Aggarwal, Jiliang Tang:
Epidemic Graph Convolutional Network. WSDM 2020: 160-168 - [c10]Xiaoyang Wang, Yao Ma, Yiqi Wang, Wei Jin, Xin Wang, Jiliang Tang, Caiyan Jia, Jian Yu:
Traffic Flow Prediction via Spatial Temporal Graph Neural Network. WWW 2020: 1082-1092 - [i17]Wenqi Fan, Tyler Derr, Xiangyu Zhao, Yao Ma, Hui Liu, Jianping Wang, Jiliang Tang, Qing Li:
Attacking Black-box Recommendations via Copying Cross-domain User Profiles. CoRR abs/2005.08147 (2020) - [i16]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) - [i15]Yiqi Wang, Yao Ma, Charu C. Aggarwal, Jiliang Tang:
Non-IID Graph Neural Networks. CoRR abs/2005.12386 (2020) - [i14]Yao Ma, Xiaorui Liu, Tong Zhao, Yozen Liu, Jiliang Tang, Neil Shah:
A Unified View on Graph Neural Networks as Graph Signal Denoising. CoRR abs/2010.01777 (2020) - [i13]Wei Jin, Tyler Derr, Yiqi Wang, Yao Ma, Zitao Liu, Jiliang Tang:
Node Similarity Preserving Graph Convolutional Networks. CoRR abs/2011.09643 (2020)
2010 – 2019
- 2019
- [c9]Wenqi Fan, Tyler Derr, Yao Ma, Jianping Wang, Jiliang Tang, Qing Li:
Deep Adversarial Social Recommendation. IJCAI 2019: 1351-1357 - [c8]Yao Ma, Suhang Wang, Charu C. Aggarwal, Jiliang Tang:
Graph Convolutional Networks with EigenPooling. KDD 2019: 723-731 - [c7]Wenqi Fan, Yao Ma, Dawei Yin, Jianping Wang, Jiliang Tang, Qing Li:
Deep social collaborative filtering. RecSys 2019: 305-313 - [c6]Yao Ma, Suhang Wang, Charu C. Aggarwal, Dawei Yin, Jiliang Tang:
Multi-dimensional Graph Convolutional Networks. SDM 2019: 657-665 - [c5]Wenqi Fan, Yao Ma, Qing Li, Yuan He, Yihong Eric Zhao, Jiliang Tang, Dawei Yin:
Graph Neural Networks for Social Recommendation. WWW 2019: 417-426 - [i12]Wenqi Fan, Yao Ma, Qing Li, Yuan He, Yihong Eric Zhao, Jiliang Tang, Dawei Yin:
Graph Neural Networks for Social Recommendation. CoRR abs/1902.07243 (2019) - [i11]Yao Ma, Suhang Wang, Charu C. Aggarwal, Jiliang Tang:
Graph Convolutional Networks with EigenPooling. CoRR abs/1904.13107 (2019) - [i10]Wenqi Fan, Tyler Derr, Yao Ma, Jianping Wang, Jiliang Tang, Qing Li:
Deep Adversarial Social Recommendation. CoRR abs/1905.13160 (2019) - [i9]Yao Ma, Suhang Wang, Lingfei Wu, Jiliang Tang:
Attacking Graph Convolutional Networks via Rewiring. CoRR abs/1906.03750 (2019) - [i8]Zhiwei Wang, Yao Ma, Zitao Liu, Jiliang Tang:
R-Transformer: Recurrent Neural Network Enhanced Transformer. CoRR abs/1907.05572 (2019) - [i7]Wenqi Fan, Yao Ma, Dawei Yin, Jianping Wang, Jiliang Tang, Qing Li:
Deep Social Collaborative Filtering. CoRR abs/1907.06853 (2019) - [i6]Han Xu, Yao Ma, Haochen Liu, Debayan Deb, Hui Liu, Jiliang Tang, Anil K. Jain:
Adversarial Attacks and Defenses in Images, Graphs and Text: A Review. CoRR abs/1909.08072 (2019) - 2018
- [c4]Yao Ma, Suhang Wang, Jiliang Tang:
Local and Global Information Preserved Network Embedding. ASONAM 2018: 222-225 - [c3]Tyler Derr, Yao Ma, Jiliang Tang:
Signed Graph Convolutional Networks. ICDM 2018: 929-934 - [c2]Yao Ma, Zhaochun Ren, Ziheng Jiang, Jiliang Tang, Dawei Yin:
Multi-Dimensional Network Embedding with Hierarchical Structure. WSDM 2018: 387-395 - [i5]Yao Ma, Suhang Wang, Charu C. Aggarwal, Dawei Yin, Jiliang Tang:
Multi-dimensional Graph Convolutional Networks. CoRR abs/1808.06099 (2018) - [i4]Zhiwei Wang, Yao Ma, Dawei Yin, Jiliang Tang:
Linked Recurrent Neural Networks. CoRR abs/1808.06170 (2018) - [i3]Tyler Derr, Yao Ma, Jiliang Tang:
Signed Graph Convolutional Network. CoRR abs/1808.06354 (2018) - [i2]Yao Ma, Ziyi Guo, Zhaochun Ren, Yihong Eric Zhao, Jiliang Tang, Dawei Yin:
Dynamic Graph Neural Networks. CoRR abs/1810.10627 (2018) - 2017
- [c1]Yao Ma, Suhang Wang, Jiliang Tang:
Network Embedding with Centrality Information. ICDM Workshops 2017: 1144-1145 - [i1]Yao Ma, Suhang Wang, Zhaochun Ren, Dawei Yin, Jiliang Tang:
Preserving Local and Global Information for Network Embedding. CoRR abs/1710.07266 (2017)
Coauthor Index
Juanhui Li
aka: Juan-Hui Li
aka: Juan-Hui Li
[c54] [c53] [c52] [c51] [c50] [c48] [i48] [i47] [i39] [j5] [j4] [c38] [c35] [c34] [c33] [c32] [i35] [i34] [i31] [i30] [i28] [j3] [j2] [c28] [c27] [c26] [i27] [i26] [i25] [i23] [c25] [c24] [c23] [c22] [c21] [c20] [c19] [c18] [i21] [i20] [i19] [i18] [j1] [c17] [c16] [c15] [c13] [c12] [c11] [c10] [i17] [i16] [i15] [i14] [i13] [c9] [c8] [c7] [c6] [c5] [i12] [i11] [i10] [i9] [i8] [i7] [i6] [c4] [c3] [c2] [i5] [i4] [i3] [i2] [c1] [i1]
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To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
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Archived links via Wayback Machine
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Reference lists
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Citation data
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load citations from opencitations.net
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OpenAlex data
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last updated on 2025-12-28 00:24 CET by the dblp team
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