Yao Ma

According to our database, Yao Ma authored at least 63 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Addressing Shortcomings in Fair Graph Learning Datasets: Towards a New Benchmark.

Xiaowei Qian, Zhimeng Guo, Jialiang Li, Haitao Mao, Bingheng Li, Suhang Wang, Yao Ma

CoRR, 2024

Graph Foundation Models.

Haitao Mao, Zhikai Chen, Wenzhuo Tang, Jianan Zhao, Yao Ma, Tong Zhao, Neil Shah, Mikhail Galkin, Jiliang Tang

CoRR, 2024

A Data Generation Perspective to the Mechanism of In-Context Learning.

Haitao Mao, Guangliang Liu, Yao Ma, Rongrong Wang, Jiliang Tang

CoRR, 2024

Precedence-Constrained Winter Value for Effective Graph Data Valuation.

Hongliang Chi, Wei Jin, Charu Aggarwal, Yao Ma

CoRR, 2024

The 5th International Workshop on Machine Learning on Graphs (MLoG).

Tyler Derr, Yao Ma, Kaize Ding, Tong Zhao, Nesreen K. Ahmed

Proceedings of the 17th ACM International Conference on Web Search and Data Mining, 2024

2023

Adversarial Attacks for Black-Box Recommender Systems via Copying Transferable Cross-Domain User Profiles.

Wenqi Fan, Xiangyu Zhao, Qing Li, Tyler Derr, Yao Ma, Hui Liu, Jianping Wang, Jiliang Tang

IEEE Trans. Knowl. Data Eng., December, 2023

Customized Graph Nerual Networks.

Yiqi Wang, Yao Ma, Wei Jin, Chaozhuo Li, Charu Aggarwal, Jiliang Tang

IEEE Data Eng. Bull., 2023

Fast Graph Condensation with Structure-based Neural Tangent Kernel.

Lin Wang, Wenqi Fan, Jiatong Li, Yao Ma, Qing Li

CoRR, 2023

Adaptive Pairwise Encodings for Link Prediction.

Harry Shomer, Yao Ma, Haitao Mao, Juanhui Li, Bo Wu, Jiliang Tang

CoRR, 2023

Revisiting Link Prediction: A Data Perspective.

Haitao Mao, Juanhui Li, Harry Shomer, Bingheng Li, Wenqi Fan, Yao Ma, Tong Zhao, Neil Shah, Jiliang Tang

CoRR, 2023

Multi-Instance Adversarial Attack on GNN-Based Malicious Domain Detection.

Mahmoud Nazzal, Issa Khalil, Abdallah Khreishah, NhatHai Phan, Yao Ma

CoRR, 2023

Improving Fairness of Graph Neural Networks: A Graph Counterfactual Perspective.

Zhimeng Guo, Jialiang Li, Teng Xiao, Yao Ma, Suhang Wang

CoRR, 2023

The 3rd International Workshop on Machine Learning on Graphs (MLoG).

Tyler Derr, Yao Ma, Benedek Rozemberczki, Neil Shah, Shirui Pan

Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining, 2023

Graph Enhanced BERT for Query Understanding.

Juanhui Li, Wei Zeng, Suqi Cheng, Yao Ma, Jiliang Tang, Shuaiqiang Wang, Dawei Yin

Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023

Demystifying Structural Disparity in Graph Neural Networks: Can One Size Fit All?

Haitao Mao, Zhikai Chen, Wei Jin, Haoyu Han, Yao Ma, Tong Zhao, Neil Shah, Jiliang Tang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Evaluating Graph Neural Networks for Link Prediction: Current Pitfalls and New Benchmarking.

Juanhui Li, Harry Shomer, Haitao Mao, Shenglai Zeng, Yao Ma, Neil Shah, Jiliang Tang, Dawei Yin

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Distance-Based Propagation for Efficient Knowledge Graph Reasoning.

Harry Shomer, Yao Ma, Juanhui Li, Bo Wu, Charu C. Aggarwal, Jiliang Tang

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Towards Fair Graph Neural Networks via Graph Counterfactual.

Zhimeng Guo, Jialiang Li, Teng Xiao, Yao Ma, Suhang Wang

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

Learning Representations for Hyper-Relational Knowledge Graphs.

Harry Shomer, Wei Jin, Juanhui Li, Yao Ma, Hui Liu

Proceedings of the International Conference on Advances in Social Networks Analysis and Mining, 2023

Are Message Passing Neural Networks Really Helpful for Knowledge Graph Completion?

Juanhui Li, Harry Shomer, Jiayuan Ding, Yiqi Wang, Yao Ma, Neil Shah, Jiliang Tang, Dawei Yin

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

2022

A Graph Neural Network Framework for Social Recommendations.

Wenqi Fan, Yao Ma, Qing Li, Jianping Wang, Guoyong Cai, Jiliang Tang, Dawei Yin

IEEE Trans. Knowl. Data Eng., 2022

Negative samples selecting strategy for graph contrastive learning.

Rui Miao, Yintao Yang, Yao Ma, Xin Juan, Haotian Xue, Jiliang Tang, Ying Wang, Xin Wang

Inf. Sci., 2022

Learning Representations for Hyper-Relational Knowledge Graphs.

Harry Shomer, Wei Jin, Juan-Hui Li, Yao Ma, Jiliang Tang

CoRR, 2022

Are Graph Neural Networks Really Helpful for Knowledge Graph Completion?

Juan-Hui Li, Harry Shomer, Jiayuan Ding, Yiqi Wang, Yao Ma, Neil Shah, Jiliang Tang, Dawei Yin

CoRR, 2022

Graph Enhanced BERT for Query Understanding.

Juan-Hui Li, Yao Ma, Wei Zeng, Suqi Cheng, Jiliang Tang, Shuaiqiang Wang, Dawei Yin

CoRR, 2022

Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective.

Wei Jin, Xiaorui Liu, Yao Ma, Charu C. Aggarwal, Jiliang Tang

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Automated Self-Supervised Learning for Graphs.

Wei Jin, Xiaorui Liu, Xiangyu Zhao, Yao Ma, Neil Shah, Jiliang Tang

Proceedings of the Tenth International Conference on Learning Representations, 2022

Is Homophily a Necessity for Graph Neural Networks?

Yao Ma, Xiaorui Liu, Neil Shah, Jiliang Tang

Proceedings of the Tenth International Conference on Learning Representations, 2022

SGKD: A Scalable and Effective Knowledge Distillation Framework for Graph Representation Learning.

Yufei He, Yao Ma

Proceedings of the IEEE International Conference on Data Mining Workshops, 2022

Heterogeneous Randomized Response for Differential Privacy in Graph Neural Networks.

Khang Tran, Phung Lai, NhatHai Phan, Issa Khalil, Yao Ma, Abdallah Khreishah, My T. Thai, Xintao Wu

Proceedings of the IEEE International Conference on Big Data, 2022

2021

Node Similarity Preserving Graph Convolutional Networks.

Wei Jin, Tyler Derr, Yiqi Wang, Yao Ma, Zitao Liu, Jiliang Tang

Proceedings of the WSDM '21, 2021

Graph Neural Networks with Adaptive Residual.

Xiaorui Liu, Jiayuan Ding, Wei Jin, Han Xu, Yao Ma, Zitao Liu, Jiliang Tang

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Graph Representation Learning: Foundations, Methods, Applications and Systems.

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

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Graph Adversarial Attack via Rewiring.

Yao Ma, Suhang Wang, Tyler Derr, Lingfei Wu, Jiliang Tang

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Elastic Graph Neural Networks.

Xiaorui Liu, Wei Jin, Yao Ma, Yaxin Li, Hua Liu, Yiqi Wang, Ming Yan, Jiliang Tang

Proceedings of the 38th International Conference on Machine Learning, 2021

Attacking Black-box Recommendations via Copying Cross-domain User Profiles.

Wenqi Fan, Tyler Derr, Xiangyu Zhao, Yao Ma, Hui Liu, Jianping Wang, Jiliang Tang, Qing Li

Proceedings of the 37th IEEE International Conference on Data Engineering, 2021

Graph Feature Gating Networks.

Wei Jin, Xiaorui Liu, Yao Ma, Tyler Derr, Charu C. Aggarwal, Jiliang Tang

Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

A Unified View on Graph Neural Networks as Graph Signal Denoising.

Yao Ma, Xiaorui Liu, Tong Zhao, Yozen Liu, Jiliang Tang, Neil Shah

Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

2020

Adversarial Attacks and Defenses in Images, Graphs and Text: A Review.

Han Xu, Yao Ma, Haochen Liu, Debayan Deb, Hui Liu, Jiliang Tang, Anil K. Jain

Int. J. Autom. Comput., 2020

Non-IID Graph Neural Networks.

Yiqi Wang, Yao Ma, Charu C. Aggarwal, Jiliang Tang

CoRR, 2020

Traffic Flow Prediction via Spatial Temporal Graph Neural Network.

Xiaoyang Wang, Yao Ma, Yiqi Wang, Wei Jin, Xin Wang, Jiliang Tang, Caiyan Jia, Jian Yu

Proceedings of the WWW '20: The Web Conference 2020, Taipei, Taiwan, April 20-24, 2020, 2020

Epidemic Graph Convolutional Network.

Tyler Derr, Yao Ma, Wenqi Fan, Xiaorui Liu, Charu C. Aggarwal, Jiliang Tang

Proceedings of the WSDM '20: The Thirteenth ACM International Conference on Web Search and Data Mining, 2020

Streaming Graph Neural Networks.

Yao Ma, Ziyi Guo, Zhaochun Ren, Jiliang Tang, Dawei Yin

Proceedings of the 43rd International ACM SIGIR conference on research and development in Information Retrieval, 2020

Deep Adversarial Canonical Correlation Analysis.

Wenqi Fan, Yao Ma, Han Xu, Xiaorui Liu, Jianping Wang, Qing Li, Jiliang Tang

Proceedings of the 2020 SIAM International Conference on Data Mining, 2020

Deep Graph Learning: Foundations, Advances and Applications.

Yu Rong, Tingyang Xu, Junzhou Huang, Wenbing Huang, Hong Cheng, Yao Ma, Yiqi Wang, Tyler Derr, Lingfei Wu, Tengfei Ma

Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

Graph Structure Learning for Robust Graph Neural Networks.

Wei Jin, Yao Ma, Xiaorui Liu, Xianfeng Tang, Suhang Wang, Jiliang Tang

Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

Learning from Incomplete Labeled Data via Adversarial Data Generation.

Wentao Wang, Tyler Derr, Yao Ma, Suhang Wang, Hui Liu, Zitao Liu, Jiliang Tang

Proceedings of the 20th IEEE International Conference on Data Mining, 2020

Graph Pooling with Representativeness.

Juan-Hui Li, Yao Ma, Yiqi Wang, Charu C. Aggarwal, Chang-Dong Wang, Jiliang Tang

Proceedings of the 20th IEEE International Conference on Data Mining, 2020

2019

R-Transformer: Recurrent Neural Network Enhanced Transformer.

Zhiwei Wang, Yao Ma, Zitao Liu, Jiliang Tang

CoRR, 2019

Attacking Graph Convolutional Networks via Rewiring.

Yao Ma, Suhang Wang, Lingfei Wu, Jiliang Tang

CoRR, 2019

Graph Neural Networks for Social Recommendation.

Wenqi Fan, Yao Ma, Qing Li, Yuan He, Yihong Eric Zhao, Jiliang Tang, Dawei Yin

Proceedings of the World Wide Web Conference, 2019

Multi-dimensional Graph Convolutional Networks.

Yao Ma, Suhang Wang, Charu C. Aggarwal, Dawei Yin, Jiliang Tang

Proceedings of the 2019 SIAM International Conference on Data Mining, 2019

Deep social collaborative filtering.

Wenqi Fan, Yao Ma, Dawei Yin, Jianping Wang, Jiliang Tang, Qing Li

Proceedings of the 13th ACM Conference on Recommender Systems, 2019

Graph Convolutional Networks with EigenPooling.

Yao Ma, Suhang Wang, Charu C. Aggarwal, Jiliang Tang

Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

Deep Adversarial Social Recommendation.

Wenqi Fan, Tyler Derr, Yao Ma, Jianping Wang, Jiliang Tang, Qing Li

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

2018

Dynamic Graph Neural Networks.

Yao Ma, Ziyi Guo, Zhaochun Ren, Yihong Eric Zhao, Jiliang Tang, Dawei Yin

CoRR, 2018

Signed Graph Convolutional Network.

Tyler Derr, Yao Ma, Jiliang Tang

CoRR, 2018

Linked Recurrent Neural Networks.

Zhiwei Wang, Yao Ma, Dawei Yin, Jiliang Tang

CoRR, 2018

Multi-Dimensional Network Embedding with Hierarchical Structure.

Yao Ma, Zhaochun Ren, Ziheng Jiang, Jiliang Tang, Dawei Yin

Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining, 2018

Signed Graph Convolutional Networks.

Tyler Derr, Yao Ma, Jiliang Tang

Proceedings of the IEEE International Conference on Data Mining, 2018

Local and Global Information Preserved Network Embedding.

Yao Ma, Suhang Wang, Jiliang Tang

Proceedings of the IEEE/ACM 2018 International Conference on Advances in Social Networks Analysis and Mining, 2018

2017

Preserving Local and Global Information for Network Embedding.

Yao Ma, Suhang Wang, Zhaochun Ren, Dawei Yin, Jiliang Tang

CoRR, 2017

Network Embedding with Centrality Information.

Yao Ma, Suhang Wang, Jiliang Tang

Proceedings of the 2017 IEEE International Conference on Data Mining Workshops, 2017