Daixin Wang

According to our database, Daixin Wang authored at least 22 papers between 2015 and 2024.

Collaborative distances:

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

2024

Revisiting Adversarial Attacks on Graph Neural Networks for Graph Classification.

Xin Wang, Heng Chang, Beini Xie, Tian Bian, Shiji Zhou, Daixin Wang, Zhiqiang Zhang, Wenwu Zhu

IEEE Trans. Knowl. Data Eng., May, 2024

Optimizing Long-tailed Link Prediction in Graph Neural Networks through Structure Representation Enhancement.

Yakun Wang, Daixin Wang, Hongrui Liu, Binbin Hu, Yingcui Yan, Qiyang Zhang, Zhiqiang Zhang

CoRR, 2024

Graph Neural Network with Two Uplift Estimators for Label-Scarcity Individual Uplift Modeling.

Dingyuan Zhu, Daixin Wang, Zhiqiang Zhang, Kun Kuang, Yan Zhang, Yulin Kang, Jun Zhou

CoRR, 2024

Financial Default Prediction via Motif-preserving Graph Neural Network with Curriculum Learning.

Daixin Wang, Zhiqiang Zhang, Yeyu Zhao, Kai Huang, Yulin Kang, Jun Zhou

CoRR, 2024

Optimizing Long-tailed Link Prediction in Graph Neural Networks through Structure Representation Enhancement.

Yakun Wang, Daixin Wang, Hongrui Liu, Binbin Hu, Yingcui Yan, Qiyang Zhang, Zhiqiang Zhang

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Granola: Graph Neural Network Tackling Tabular Data for Online Loan Default Prediction.

Borui Ye, Shuo Yang, Meiqi Zhu, Binbin Hu, Daixin Wang, Zhiqiang Zhang, Youqiang He, Zhiyang Hu, Huimei He, Jun Zhou

Proceedings of the Database Systems for Advanced Applications, 2024

2023

Graph Neural Network with Two Uplift Estimators for Label-Scarcity Individual Uplift Modeling.

Dingyuan Zhu, Daixin Wang, Zhiqiang Zhang, Kun Kuang, Yan Zhang, Yulin Kang, Jun Zhou

Proceedings of the ACM Web Conference 2023, 2023

Financial Default Prediction via Motif-preserving Graph Neural Network with Curriculum Learning.

Daixin Wang, Zhiqiang Zhang, Yeyu Zhao, Kai Huang, Yulin Kang, Jun Zhou

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Unsupervised Fraud Transaction Detection on Dynamic Attributed Networks.

Yangyang Hou, Daixin Wang, Binbin Hu, Ruoyu Zhuang, Zhiqiang Zhang, Jun Zhou, Feng Zhao, Yulin Kang, Zhanwen Qiao

Proceedings of the Database Systems for Advanced Applications, 2023

Adversarially Robust Neural Architecture Search for Graph Neural Networks.

Beini Xie, Heng Chang, Ziwei Zhang, Xin Wang, Daixin Wang, Zhiqiang Zhang, Rex Ying, Wenwu Zhu

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

A Graph Learning Based Framework for Billion-Scale Offline User Identification.

Daixin Wang, Zujian Weng, Zhengwei Wu, Zhiqiang Zhang, Peng Cui, Hongwei Zhao, Jun Zhou

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

2021

Conditional Attention Networks for Distilling Knowledge Graphs in Recommendation.

Ke Tu, Peng Cui, Daixin Wang, Zhiqiang Zhang, Jun Zhou, Yuan Qi, Wenwu Zhu

CoRR, 2021

Temporal-Aware Graph Neural Network for Credit Risk Prediction.

Daixin Wang, Zhiqiang Zhang, Jun Zhou, Peng Cui, Jingli Fang, Quanhui Jia, Yanming Fang, Yuan Qi

Proceedings of the 2021 SIAM International Conference on Data Mining, 2021

Low-dimensional Alignment for Cross-Domain Recommendation.

Tianxin Wang, Fuzhen Zhuang, Zhiqiang Zhang, Daixin Wang, Jun Zhou, Qing He

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

Conditional Graph Attention Networks for Distilling and Refining Knowledge Graphs in Recommendation.

Ke Tu, Peng Cui, Daixin Wang, Zhiqiang Zhang, Jun Zhou, Yuan Qi, Wenwu Zhu

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

2019

RNE: A Scalable Network Embedding for Billion-Scale Recommendation.

Jianbin Lin, Daixin Wang, Lu Guan, Yin Zhao, Binqiang Zhao, Jun Zhou, Xiaolong Li, Yuan (Alan) Qi

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2019

A Semi-Supervised Graph Attentive Network for Financial Fraud Detection.

Daixin Wang, Yuan Qi, Jianbin Lin, Peng Cui, Quanhui Jia, Zhen Wang, Yanming Fang, Quan Yu, Jun Zhou, Shuang Yang

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

2018

Deep Variational Network Embedding in Wasserstein Space.

Dingyuan Zhu, Peng Cui, Daixin Wang, Wenwu Zhu

Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Deep Asymmetric Transfer Network for Unbalanced Domain Adaptation.

Daixin Wang, Peng Cui, Wenwu Zhu

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2016

Structural Deep Network Embedding.

Daixin Wang, Peng Cui, Wenwu Zhu

Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016

2015

Learning Compact Hash Codes for Multimodal Representations Using Orthogonal Deep Structure.

Daixin Wang, Peng Cui, Mingdong Ou, Wenwu Zhu

IEEE Trans. Multim., 2015

Deep Multimodal Hashing with Orthogonal Regularization.

Daixin Wang, Peng Cui, Mingdong Ou, Wenwu Zhu

Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015