Yilun Jin
Cited by
Cited by
Secureboost: A lossless federated learning framework
K Cheng, T Fan, Y Jin, Y Liu, T Chen, D Papadopoulos, Q Yang
IEEE Intelligent Systems 36 (6), 87-98, 2021
Towards Utilizing Unlabeled Data in Federated Learning: A Survey and Prospective
Y Jin, X Wei, Y Liu, Q Yang
arXiv preprint arXiv:2002.11545, 2020
Dane: Domain adaptive network embedding
Y Zhang, G Song, L Du, S Yang, Y Jin
Proceedings of the Twenty-Eighth International Conference on International …, 2019
Graph Structural-topic Neural Network
Q Long*, Y Jin*, G Song, Y Li, W Lin
Proceedings of the 26th ACM SIGKDD International Conference on Knowledge …, 2020
GraLSP: Graph Neural Networks with Local Structural Patterns.
Y Jin, G Song, C Shi
The Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI), 4361-4368, 2020
Hierarchical Community Structure Preserving Network Embedding: A Subspace Approach
Q Long, Y Wang, L Du, G Song, Y Jin, W Lin
Proceedings of the 28th ACM International Conference on Information and …, 2019
Selective Cross-City Transfer Learning for Traffic Prediction via Source City Region Re-Weighting
Y Jin, K Chen, Q Yang
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022
Domain Adaptive Classification on Heterogeneous Information Networks.
S Yang, G Song, Y Jin, L Du
IJCAI, 1410-1416, 2020
Theoretically Improving Graph Neural Networks via Anonymous Walk Graph Kernels
Q Long*, Y Jin*, Y Wu*, G Song
Proceedings of the Web Conference 2021, 1204-1214, 2021
GraphMSE: Efficient Meta-path Selection in Semantically Aligned Feature Space for Graph Neural Networks
Y Li, Y Jin, G Song, Z Zhu, C Shi, Y Wang
Proceedings of the AAAI Conference on Artificial Intelligence 35 (5), 4206-4214, 2021
A Survey on Vertical Federated Learning: From a Layered Perspective
L Yang, D Chai, J Zhang, Y Jin, L Wang, H Liu, H Tian, Q Xu, K Chen
arXiv preprint arXiv:2304.01829, 2023
Scalable and Efficient Full-Graph GNN Training for Large Graphs
X Wan, K Xu, X Liao, Y Jin, K Chen, X Jin
Proceedings of the ACM on Management of Data 1 (2), 1-23, 2023
Data Resampling for Federated Learning with Non-IID Labels
Z Tang, Z Hu, S Shi, Y Cheung, Y Jin, Z Ren, X Chu
IJCAI International Workshop on Federated and Transfer Learning (FTL-IJCAI'21), 2021
Transferable Graph Structure Learning for Graph-based Traffic Forecasting Across Cities
Y Jin, K Chen, Q Yang
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and …, 2023
Federated Learning without Full Labels: A Survey
Y Jin, Y Liu, K Chen, Q Yang
IEEE Data Engineering Bulletin 46 (1), 27-51, 2023
Secure Forward Aggregation for Vertical Federated Neural Networks
S Cai, D Chai, L Yang, J Zhang, Y Jin, L Wang, K Guo, K Chen
IJCAI International Workshop on Trustworthy Federated Learning (FL-IJCAI'22), 2022
EPNE: Evolutionary Pattern Preserving Network Embedding
J Wang*, Y Jin*, G Song, X Ma
Proceedings of the 24th European Conference on Artificial Intelligence, 1603 …, 2020
Ternary Hashing
C Liu, L Fan, KW Ng, Y Jin, C Ju, T Zhang, CS Chan, Q Yang
arXiv preprint arXiv:2103.09173, 2021
Deep convolutional neural network based medical concept normalization
G Song, Q Long, Y Luo, Y Wang, Y Jin
IEEE Transactions on Big Data 8 (5), 1195-1208, 2020
Active Domain Transfer on Network Embedding
L Jin, Y Zhang, G Song, Y Jin
Proceedings of The Web Conference 2020, 2683-2689, 2020
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