Publications

2024

1. CIKM

   Federated Node Classification over Distributed Ego-Networks with Secure Contrastive Embedding Sharing

   Han Xie, Li Xiong, and Carl Yang

   In Proceedings of the ACM International Conference on Information and Knowledge Management, 2024
2. SPIE

   Federated learning for cross-institution brain network analysis (Oral, *Co-first Authors)

   Han Xie*, Yi Yang*, Hejie Cui, and Carl Yang

   In Medical Imaging 2024: Computer-Aided Diagnosis. SPIE, 2024

   PDF
3. PSB

   FedBrain: Federated Training of Graph Neural Networks for Connectome-based Brain Imaging Analysis

   Yi Yang, Han Xie, Hejie Cui, and Carl Yang

   In Proceedings of the Pacific Symposium on Biocomputing, 2024

   PDF

2023

1. ICDM-FedGraph

   Personalized Federated Learning for Graph Classification via Client Graph Learning

   Jiachen Zhou, Han Xie, and Carl Yang

   Workshop on Federated Learning with Graph Data: The IEEE International Conference on Data Mining, 2023
2. KDD

   Graph-Aware Language Model Pre-Training on a Large Graph Corpus Can Help Multiple Graph Applications (Oral)

   Han Xie, Da Zheng, Jun Ma, Houyu Zhang, Vassilis N. Ioannidis, Xiang Song, Qing Ping, Sheng Wang, Carl Yang, Yi Xu, Belinda Zeng, and Trishul Chilimbi

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

   PDF
3. WWW

   Federated Node Classification over Graphs with Latent Link-type Heterogeneity (Oral)

   Han Xie, Li Xiong, and Carl Yang

   In Proceedings of the ACM Web Conference, 2023

   PDF

2022

1. CIKM-FedGraph

   Subgraph Federated Learning over Heterogeneous Graphs

   Ke Zhang, Han Xie, Zishan Gu, Xiaoxiao Li, Lichao Sun, Siu Ming Yiu, Yuan Yao, and Carl Yang

   Workshop on Federated Learning with Graph Data: The ACM International Conference on Information and Knowledge Management, 2022

2021

1. NeurIPS

   Federated Graph Classification over Non-iid Graphs

   Han Xie, Jing Ma, Li Xiong, and Carl Yang

   In Proceedings of the Conference on Neural Information Processing Systems, 2021

   PDF
2. ICLRW/MLSysW

   Fedgraphnn: A Federated Learning System and Benchmark for Graph Neural Networks

   Chaoyang He, Keshav Balasubramanian, Emir Ceyani, Carl Yang, Han Xie, Lichao Sun, Lifang He, Liangwei Yang, Philip S Yu, Yu Rong, and  others

   Workshop on Distributed and Private Machine Learning: The International Conference on Learning Representations (ICLR-DPML). Workshop on Graph Neural Networks and Systems: The Conference on Machine Learning and Systems (MLSys-GNNSys), 2021

   arXiv

2019

1. WABI

   Detecting Transcriptomic Structural Variants in Heterogeneous Contexts via the Multiple Compatible Arrangements Problem

   Yutong Qiu, Cong Ma, Han Xie, and Carl Kingsford

   In Proceedings of the International Workshop on Algorithms in Bioinformatics, 2019