Jinjing Zhu, Feiyang Ye, Qiao Xiao, Pengxin Guo, Yu Zhang, Qiang Yang. A Unified Framework for Unsupervised Domain Adaptation based on Instance Weighting. To appear in IEEE Transactions on Image Processing (TIP), 2024.

Feiyang Ye, Baijiong Lin, Zhixiong Yue, Yu Zhang, and Ivor W. Tsang. Multi-Objective Meta-Learning. Artificial Intelligence (AIJ), 2024

Baijiong Lin, Feiyang Ye, Yu Zhang, and Ivor W. Tsang. Reasonable Effectiveness of Random Weighting: A Litmus Test for Multi-Task Learning. Transactions on Machine Learning Research (TMLR), 2022

Jinliang Deng, Feiyang Ye, Du Yin, Xuan Song, Ivor W. Tsang, and Hui Xiong. Parsimony or Capability? Decomposition Delivers Both in Long-term Time Series Forecasting. In Conference on Neural Information Processing Systems (NeurIPS), 2024, spotlight.

Xiang Liu, Liangxi Liu, Feiyang Ye, Yunheng Shen, Xia Li, Linshan Jiang, Jialin Li. FedLPA: Personalized One-shot Federated Learning with Layer-Wise Posterior Aggregation. In Conference on Neural Information Processing Systems (NeurIPS), 2024.

Feiyang Ye, Baijiong Lin, Xiaofeng Cao, Yu Zhang, and Ivor W. Tsang. A First-Order Multi-Gradient Algorithm for Multi-Objective Bi-Level Optimization. In European Conference on Artificial Intelligence (ECAI), 2024.

Feiyang Ye^*, Yueming Lyu^*, Xuehao Wang, Yu Zhang, and Ivor W. Tsang. Adaptive Stochastic Gradient Algorithm for Black-box Multi-Objective Learning. In International Conference on Learning Representations (ICLR), 2024

Yang Li, Zelin Wu, and Feiyang Ye. Evolutionary Neural Networks for Option Pricing: Multi-Assets Option and Exotic Option. In Proceedings of the AAAI Symposium Series, 2023

Feiyang Ye^*, Xuehao Wang^*, Yu Zhang, and Ivor W. Tsang. Multi-Task Learning via Time-Aware Neural ODE. In International Joint Conference on Artificial Intelligence (IJCAI), 2023

Feiyang Ye^*, Jianghan Bao^*, Yu Zhang. Partially-Labeled Domain Generalization via Multi-Dimensional Domain Adaptation. In International Joint Conference on Neural Networks (IJCNN), 2023

Feiyang Ye^*, Baijiong Lin^*, Zhixiong Yue, Pengxin Guo, Qiao Xiao, Yu Zhang. Multi-Objective Meta Learning. In Conference on Neural Information Processing Systems (NeurIPS), 2021

Feiyang Ye^*, Yueming Lyu^*, Xuehao Wang, Masashi Sugiyama, Yu Zhang, and Ivor W. Tsang. Sharpness-Aware Black-Box Optimization. Preprint.

Xuehao Wang, Feiyang Ye, and Yu Zhang. Task-Aware Low-Rank Adaptation of Segment Anything Model. Preprint.

Baijiong Lin, Weisen Jiang, Feiyang Ye, Yu Zhang, Pengguang Chen, Ying-Cong Chen, Shu Liu, James Kwok. Dual-Balancing for Multi-Task Learning. Preprint.

Zhixiong Yue^*, Feiyang Ye^*, Yu Zhang, Christy Liang, Ivor W. Tsang. Deep Safe Multi-Task Learning. Preprint.

IEEE Transactions on Pattern Analysis and Machine Intelligence (T-PAMI)

IEEE Transactions on Emerging Topics in Computational Intelligence (TETCI)

Neural Information Processing Systems (NeurIPS): 2024

International Conference on Learning Representations (ICLR): 2025

International Conference on Artificial Intelligence and Statistics (AISTATS): 2025

European Conference on Machine Learning (ECML): 2024

RIKEN-AIP Overseas Student Collaboration Program / Supervised by Prof. Masashi Sugiyama .