Publications

-2023-

X. Tan & H. Yu, "Hire When You Need to: Gradual Participant Recruitment for Auction-based Federated Learning," arXiv preprint arXiv:2310.02651, 2023.
X. Tan, W. Y. B. Lim, D. Niyato & H. Yu, "Reputation-Aware Opportunistic Budget Optimization for Auction-based Federation Learning," in Proceedings of the 2023 International Joint Conference on Neural Networks (IJCNN'23), doi:10.1109/IJCNN54540.2023.10191418, 2023.
S. Chen, X. Tan, Y. Yu, W. Y. Lim, Zehui Xiong, and Han Yu, "Privacy budget-aware incentive mechanism for federated learning in intelligent transportation systems", in Proceedings of IEEE International Conference on Communications (ICC), Rome, Italy, May 2023.

Tan, X., Ng, W. C., Lim, W. Y. B., Xiong, Z., Niyato, D. & Yu, H. Reputation-aware federated learning client selection based on stochastic integer programming. IEEE Transactions on Big Data, doi:10.1109/TBDATA.2022.3191332, IEEE (2022).

Kannappan, Vinayak Teoh and Fernando, Owen Noel Newton and Chattopadhyay, Anupam and Tan, Xavier and Hong, Jeffrey Yan Jack and Seah, Hock Soon and Lye, Hui En, "La Petite Fee Cosmo: Learning Data Structures Through Game-Based Learning," 2019 International Conference on Cyberworlds (CW), Kyoto, Japan, 2019, pp. 207-210, doi: 10.1109/CW.2019.00041.