Publications

In Submission

1. Xingyu Li,, Bo. Tang, “G-Mix: A Generalized Mixup Learning Framework Towards Flat Minima”. Submitted for publication.

Featured Publications

1. Xingyu Li,, Bo. Tang, and Haifeng. Li, “AdaER: An Adaptive Experience Replay Approach for Continual Lifelong Learning”. Neurocomputing 2023. (CCF C)

2. Chen Qiu*, Xingyu Li*, Chaithanya Kumar Mummadi, Madan Ravi Ganesh, Zhenzhen Li, Lu Peng, Wan-Yi Lin, “Text-driven Prompt Generation for Vision-Language Models in Federated Learning”. FL@FM-NeurIPS’23 Oral. *Equal contribution

3. Xingyu Li, Zhe Qu, Bo Tang, and Zhuo Lu, “FedLGA: Towards System-Heterogeneity of Federated Learning via Local Gradient Approximation”. IEEE Transactions on Cybernetics, 2023 (Early Access). (CCF B)

4. Zhe Qu, Xingyu Li, Xiao Han, Rui Duan, Keyu Chen, Shangqing Zhao, and Lixing Chen, “How to Prevent the Poor Performance Clients for Personalized Federated Learning?” IEEE / CVF Computer Vision and Pattern Recognition Conference (CVPR), June 2023. (CCF A)

5. Xingyu Li, Zhe Qu, Shangqing Zhao, Bo Tang, Zhuo Lu, and Yao Liu, “LoMar: A Local Defense Against Poisoning Attack on Federated Learning”. IEEE Transactions on Dependable and Secure Computing, 2021 (Early Access). (CCF A)
6. Zhe Qu*, Xingyu Li*, Rui Duan, Yao Liu, Bo Tang and Zhuo Lu, “Generalized Federated Learning via Sharpness Aware Minimization”. In International Conference on Machine Learning (ICML), 2022. (CCF A) *Equal contribution
7. Zhe Qu*, Xingyu Li*, Jie Xu, Bo Tang, Zhuo Lu, and Yao Liu, “On the Convergence of Multi-Server Federated Learning with Overlapping Area”. IEEE Transactions on Mobile Computing, 2022 (Early Access). (CCF A) *Equal contribution
8. Xingyu Li, Zhe Qu, Bo Tang, and Zhuo Lu. “Stragglers are not disaster: A hybrid federated learning algorithm with delayed gradients”, International Conference on Machine Learning and Applications (ICMLA), 2021.