Publications

Tutorials

• Yao Ma, Yiqi Wang, Tyler Derr, Lingfei Wu, Tengfei Ma, Yu Rong, Tingyang Xu, Junzhou Huang, Wenbing Huang, Hong Cheng
  Deep Graph Learning: Foundations, Advances and Applications
  In Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD), 2020

• Yao Ma, Wei Jin, Jiliang Tang, Lingfei Wu, Tengfei Ma
  Graph Neural Networks: Models and Applications
  AAAI Tutorial Forum, 2020

Books or Book Chapters

• Yao Ma and Jiliang Tang
  Deep Learning on Graphs
  Cambridge University Press, 2021

• Yao Ma, Charu Aggarwal, Jiliang Tang
  Feature Engineering For Data Streams
  Book Chapter in Feature Engineering for Machine Learning and Data Analytics, CRC Press, 2017

Preprints

• 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

• Hongliang Chi, Jin Wei, Charu Aggarwal, Yao Ma
  Precedence-Constrained Winter Value for Effective Graph Data Valuation

• Haitao Mao, Guangliang Liu, Yao Ma, Rongrong Wang, Jiliang Tang
  A Data Generation Perspective to the Mechanism of In-Context Learning

• Hongjia Xu, Liangliang Zhang, Yao Ma, Sheng Zhou, Zhuonan Zheng, Bu Jiajun
  A Survey on Graph Condensation

• Tianyi Zhao, Liangliang Zhang, Yao Ma, Lu Cheng
  A Survey on Safe Multi-Modal Learning System

• Yiqi Wang, Yao Ma, Charu Aggarwal, Jiliang Tang
  Non-IID Graph Neural Networks

• Zhiwei Wang, Yao Ma, Zitao Liu, Jiliang Tang
  R-Transformer: Recurrent Neural Network Enhanced Transformer [code]

• Zhiwei Wang, Yao Ma, Dawei Yin, Jiliang Tang
  Linked Reccurent Neural Networks

• Yao Ma, Suhang Wang, Zhaochun Ren, Dawei Yin, Jiliang Tang
  Preserving Local and Global Inoformation for Network Embedding

Conference and Journal Publications

• Tainyi Zhao, Liangliang Zhang, Yao Ma, Lu Cheng.
  A Survey on Safe Multi-Modal Learning Systems.
  In Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining(SIGKDD), 2024

• 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.
  In Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining(SIGKDD), 2024

• Harry Shomer, Yao Ma, Haitao Mao, Juanhui Li, Bo Wu, Jiliang Tang
  LPFormer: An Adaptive Graph Transformer for Link Prediction.
  In Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining(SIGKDD), 2024

• Hongliang Chi, Yao Ma
  Enhancing Graph Contrastive Learning with Node Similarity.
  In Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining(SIGKDD), 2024

• Haitao Mao, Zhikai Chen, Wenzhuo Tang, Jianan Zhao, Yao Ma, Tong Zhao, Neil Shah, Mikhail Galkin, Jiliang Tang
  Graph Foundation Models
  In Proceedings of the 41th International Conference on Machine Learning (ICML), 2024.

• 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.
  In Proceedings of the 41th International Conference on Machine Learning (ICML), 2024.

• Lin Wang, Wenqi Fan, Jiatong Li, Yao Ma, Qing Li
  Fast Graph Condensation with Structure-based Neural Tangent Kernel
  In The Web Conference (WWW 2024), 2024.

• Hongliang Chi, Cong Qi, Suhang Wang, Yao Ma
  Active Learning for Graphs with Noisy Structures
  In Proceedings of SIAM International Conference on Data Mining (SDM), 2024

• 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?
  In Thirty-seventh Conference on Neural Information Processing Systems, Orleans, United States, 2023

• 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
  In Thirty-seventh Conference on Neural Information Processing Systems, Orleans, United States, 2023

• Zhimeng Guo, Jialiang Li, Teng Xiao, Yao Ma, and Suhang Wang
  Towards Fair Graph Neural Networks via Graph Counterfactual
  In Proceedings of 32nd ACM International Conference on Information and Knowledge Management (CIKM 2023)

• Mahmoud Nazzal, Issa Khalil, Abdallah Khreishah, NhatHai Phan, Yao Ma
  Multi-Instance Adversarial Attack on GNN-Based Malicious Domain Detection
  To Appear in the 45th IEEE Symposium on Security and Privacy, May 20-23, 2024.

• Harry Shomer, Wei Jin, Juanhui Li, and Yao Ma, Jiliang Tang
  Learning Representations for Hyper-Relational Knowledge Graphs
  The 2023 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, Marrakesh, Morocco, 6-9 November 2023

• Juanhui Li, Harry Shomer, Jiayuan Ding, and Yiqi Wang, Yao Ma, Neil Shah, Jiliang Tang, Dawei Yin
  Are Graph Neural Networks Really Helpful for Knowledge Graph Completion?
  Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics, ACL 2023, Toronto, Cananda, 2023

• Juanhui Li, Yao Ma, Wei Zeng, Suqi Cheng, Jiliang Tang, Shuaiqiang Wang, Dawei Yin
  Graph Enhanced BERT for Query Understanding
  Proceedings of the 46th International ACM SIGIR conference on research and development in Information Retrieval, SIGIR 2023.

• Khang Tran, Phung Lai, NhatHai Phan, Yao Ma, Abdallah Khreishah, Issa Khalil, My T. Thai, Xintao Wu.
  Heterogeneous Randomized Response for Differential Privacy in Graph Neural Networks
  In Proceedings of the 2022 IEEE International Conference on Big Data, 2022

• Wei Jin, Xiaorui Liu, Yao Ma, Charu Aggarwal, Jiliang Tang.
  Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective
  In Proceedings of 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD 2022)

• Yao Ma, Xiaorui Liu, Neil Shah, Jiliang Tang
  Is Homophily a Necessity for Graph Neural Networks
  International Conference on Learning Representations (ICLR 2022)

• Wei Jin, Xiaorui Liu, Xiangyu Zhao, Yao Ma, Neil Shah, Jiliang Tang
  Automated Self-Supervised Learning for Graphs
  International Conference on Learning Representations (ICLR 2022)

• Xiaorui Liu, Jiayuan Jin, Wei Jin, Han Xu, Yao Ma, Zitao Liu, Jiliang Tang
  Graph Neural Networks with Adaptive Residual
  Conference on Neural Information Processing Systems (NeurIPS 2021)

• Yao Ma, Xiaorui Liu, Tong Zhao, Yozen Liu, Jiliang Tang
  A Unified View of Graph Neural Networks as Graph Signal Denoising
  In Proceedings of the 2021 ACM on Conference on Information and Knowledge Management (CIKM), 2021

• Wei Jin, Xiaorui Liu, Yao Ma, Tyler Derr, Charu Aggarwal, Jiliang Tang
  Graph Feature Gating Networks
  In Proceedings of the 2021 ACM on Conference on Information and Knowledge Management (CIKM), 2021

• Yao Ma, Suhang Wang, Tyler Derr, Lingfei Wu, Jiliang Tang
  Attacking Graph Convolutional Networks via Rewiring
  In Proceedings of 27th ACM SIGKDDConference on Knowledge Discovery and Data Mining (SIGKDD), 2021

• Xiaorui Liu, Wei Jin, Yao Ma, Yaxin Li, Hua Liu, Yiqi Wang, Ming Yan, Jiliang Tang.
  Elastic Graph Neural Networks.
  International Conference on Machine Learning (ICML), 2021.

• Wenqi Fan, Tyler Derr, Xiangyu Zhao, Yao Ma, Hui Liu, Jianping Wang, Jiliang Tang, Qing Li.
  CopyAttack: Attacking Black-box Recommendations via Copying Cross-domain User Profiles.
  In Proceedings of the IEEE 37th International Conference on Data Engineering (ICDE), 2021.

• Yao Ma, Juanhui Li, Yiqi Wang, Charu Aggarwal, Changdong Wang, Jiliang Tang
  Graph Pooling with Representativeness
  To appear in Proceedings of 20th IEEE International Conference on Data Mining (ICDM), 2020

• Wentao Wang, Tyler Derr, Yao Ma, Suhang Wang, Hui Liu, Zitao Liu, Jiliang Tang
  Learning from Incomplete Labeled Data via Adversarial Data Generation
  To appear in Proceedings of 20th IEEE International Conference on Data Mining (ICDM), 2020

• Wei Jin, Yao Ma, Xiaorui Liu, Xianfeng Tang, Suhang Wang, Jiliang Tang
  Graph Structure Learning for Robust Graph Neural Networks [code]
  In Proceedings of 26th ACM SIGKDDConference on Knowledge Discovery and Data Mining (SIGKDD),2020

• Wenqi Fan, Yao Ma, Qing Li, Yuan He, Eric Zhao, Jiliang Tang, Dawei Yin
  A Graph Neural Network Framework for Social Recommendations
  IEEE Transactions on Knowledge and Data Engineering. 2020 Jul 13.

• Yao Ma, Ziyi Ding, Zhaochun Ren, Jiliang Tang, Dawei Yin
  Streamining Graph Neural Networks
  In Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2020

• 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
  In Proceedings of the 29th International Conference on World Wide Web Companion (WWW), 2020

• Wenqi Fan, Yao Ma, Han Xu, Xiaorui Liu, Jianping Wang, Qing Li, Jiliang Tang
  Deep Adversarial Canonical Correlation Analysis
  In Proceedings of the 2020 SIAM International Conference on Data Mining (SDM 2020), 2020.

• Tyler Derr, Yao Ma, Wenqi Fan, Xiaorui Liu, Charu Aggarwal, Jiliang Tang
  Epidemic Graph Convolutional Networks [code]
  In Proceedings of 13th ACM Conference on Web Search and Data Mining (WSDM), 2020

• Wenqi Fan, Yao Ma, Dawei Yin, Jianping Wang, Jiliang Tang, Qing Li
  Deep Social Collaborative Filtering
  In Proceedings of the 13th ACM Conference on Recommender Systems (RecSys), 2019

• Han Xu, Yao Ma, Haochen Liu, Debayan Deb, Hui Liu, Jiliang Tang, Anil Jain
  Adversarial Attacks and Defenses in Images, Graphs and Text: A Review
  International Journal of Automation and Computing, 17(2), pp.151-178.

• Wenqi Fan, Tyler Derr, Yao Ma, Jianping Wang, Jiliang Tang, Qing Li
  Deep Adversarial Social Recommendation
  In Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), 2019

• Yao Ma, Suhang Wang, Charu C. Aggarwal, Jiliang Tang
  Graph Convolutional Networks with EigenPooling [code]
  In Proceedings of 25th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD), 2019

• Wenqi Fan, Yao Ma, Qing Li, Yuan He, Eric Zhao, Jiliang Tang, Dawei Yin
  Graph Neural Networks for Social Recommendation [code]
  In Proceedings of the 28th International Conference on World Wide Web Companion, 2019

• Yao Ma, Suhang Wang, Charu C. Aggarwal, Dawei Yin, Jiliang Tang
  Multi-dimensional Graph Convolutional Networks
  In Proceedings of SIAM International Conference on Data Mining (SDM), 2019

• Tyler Derr, Yao Ma, Jiliang Tang
  Signed Graph Convolutional Neural Networks [code]
  In Proceedings of the IEEE International Conference on Data Mining (ICDM), 2018

• Yao Ma, Suhang Wang, Jiliang Tang
  Local and Global Information Preserved Network Embedding
  In Proceedings of IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), 2018

• Yao Ma, Zhaochun Ren, Ziheng Jiang, Dawei Yin, Jiliang Tang
  Multidimensional Network Embedding with Hierarchical Structures
  In Proceedings of the 11th ACM International Conference on Web Search and Data Mining (WSDM), 2018

• Yao Ma, Suhang Wang, Jiliang Tang
  Network Embedding with Centrality Information
  Ph.D Forum, The IEEE International Conference on Data Mining (ICDM), 2017