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ORCIDJieming Bian
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2020 – today
- 2026
[c11]Jieming Bian, Lei Wang, Letian Zhang, Jie Xu:
FedALT: Federated Fine-Tuning Through Adaptive Local Training with Rest-of-World LoRA. AAAI 2026: 19728-19736- [i19]Jieming Bian, Lei Wang, Letian Zhang, Jie Xu:
FedTreeLoRA: Reconciling Statistical and Functional Heterogeneity in Federated LoRA Fine-Tuning. CoRR abs/2603.13282 (2026) - 2025
- [j5]Jieming Bian
, Cong Shen, Mingzhe Chen, Jie Xu:
Indirect-Communication Federated Learning via Mobile Transporters. IEEE Trans. Mob. Comput. 24(6): 4845-4857 (2025) - [c10]Jieming Bian, Lei Wang, Letian Zhang, Jie Xu:
LoRA-FAIR: Federated LoRA Fine-Tuning with Aggregation and Initialization Refinement. ICCV 2025: 3737-3746 - [c9]Lei Wang, Jieming Bian, Letian Zhang, Jie Xu:
Adaptive LoRA Experts Allocation and Selection for Federated Fine-Tuning. NeurIPS 2025 - [i18]Jieming Bian, Lei Wang, Letian Zhang, Jie Xu:
FedALT: Federated Fine-Tuning through Adaptive Local Training with Rest-of-the-World LoRA. CoRR abs/2503.11880 (2025) - [i17]Jieming Bian, Yuanzhe Peng, Lei Wang, Yin Huang, Jie Xu:
A Survey on Parameter-Efficient Fine-Tuning for Foundation Models in Federated Learning. CoRR abs/2504.21099 (2025) - [i16]Yuanzhe Peng, Jieming Bian, Lei Wang, Yin Huang, Jie Xu:
Multimodal Federated Learning: A Survey through the Lens of Different FL Paradigms. CoRR abs/2505.21792 (2025) - [i15]Lei Wang, Jieming Bian, Letian Zhang, Jie Xu:
Adaptive LoRA Experts Allocation and Selection for Federated Fine-Tuning. CoRR abs/2509.15087 (2025) - [i14]Letian Zhang, Bo Chen, Jieming Bian, Lei Wang, Jie Xu:
FedEL: Federated Elastic Learning for Heterogeneous Devices. CoRR abs/2509.16902 (2025) - 2024
- [j4]Heqiang Wang, Jieming Bian, Jie Xu:
On the Local Cache Update Rules in Streaming Federated Learning. IEEE Internet Things J. 11(6): 10808-10816 (2024) - [j3]Yuanzhe Peng, Yusen Wu, Jieming Bian, Jie Xu:
Hybrid Federated Learning for Multimodal IoT Systems. IEEE Internet Things J. 11(21): 34055-34064 (2024) - [j2]Jieming Bian, Lei Wang, Kun Yang, Cong Shen, Jie Xu:
Accelerating Hybrid Federated Learning Convergence Under Partial Participation. IEEE Trans. Signal Process. 72: 3258-3271 (2024) - [j1]Jieming Bian, Jie Xu:
Accelerating Asynchronous Federated Learning Convergence via Opportunistic Mobile Relaying. IEEE Trans. Veh. Technol. 73(7): 10668-10680 (2024) - [c8]Jieming Bian, Lei Wang, Shaolei Ren, Jie Xu:
CAFE: Carbon-Aware Federated Learning in Geographically Distributed Data Centers✱. e-Energy 2024 - [c7]Yuanzhe Peng, Jieming Bian, Jie Xu:
Fedmm: Federated Multi-Modal Learning with Modality Heterogeneity in Computational Pathology. ICASSP 2024: 1696-1700 - [c6]Lei Wang, Jieming Bian, Jie Xu:
Federated Learning with Instance-Dependent Noisy Label. ICASSP 2024: 8916-8920 - [c5]Lei Wang, Jieming Bian, Jie Xu:
Adaptive User-Centric Entanglement Routing in Quantum Data Networks. ICDCS 2024: 1202-1212 - [c4]Lei Wang, Jieming Bian, Letian Zhang, Chen Chen, Jie Xu:
Taming Cross-Domain Representation Variance in Federated Prototype Learning with Heterogeneous Data Domains. NeurIPS 2024 - [i13]Yuanzhe Peng, Jieming Bian, Jie Xu:
FedMM: Federated Multi-Modal Learning with Modality Heterogeneity in Computational Pathology. CoRR abs/2402.15858 (2024) - [i12]Lei Wang, Jieming Bian, Letian Zhang, Chen Chen, Jie Xu:
Taming Cross-Domain Representation Variance in Federated Prototype Learning with Heterogeneous Data Domains. CoRR abs/2403.09048 (2024) - [i11]Heqiang Wang, Jieming Bian, Lei Wang:
Computation and Communication Efficient Lightweighting Vertical Federated Learning. CoRR abs/2404.00466 (2024) - [i10]Jieming Bian, Lei Wang, Jie Xu:
Prioritizing Modalities: Flexible Importance Scheduling in Federated Multimodal Learning. CoRR abs/2408.06549 (2024) - [i9]Jieming Bian, Lei Wang, Letian Zhang, Jie Xu:
LoRA-FAIR: Federated LoRA Fine-Tuning with Aggregation and Initialization Refinement. CoRR abs/2411.14961 (2024) - 2023
- [c3]Jieming Bian, Jie Xu:
Mobility-Assisted Federated Learning for Vehicular Edge Computing. ACSSC 2023: 289-293 - [c2]Jieming Bian, Cong Shen, Jie Xu:
Federated Learning via Indirect Server-Client Communications. CISS 2023: 1-5 - [c1]Jieming Bian, Jie Xu:
Client Clustering for Energy-Efficient Clustered Federated Learning in Wireless Networks. UbiComp/ISWC Adjunct 2023: 718-723 - [i8]Jieming Bian, Cong Shen, Jie Xu:
Federated Learning via Indirect Server-Client Communications. CoRR abs/2302.07323 (2023) - [i7]Heqiang Wang, Jieming Bian, Jie Xu:
On the Local Cache Update Rules in Streaming Federated Learning. CoRR abs/2303.16340 (2023) - [i6]Jieming Bian, Lei Wang, Kun Yang, Cong Shen, Jie Xu:
Accelerating Hybrid Federated Learning Convergence under Partial Participation. CoRR abs/2304.05397 (2023) - [i5]Jieming Bian, Cong Shen, Jie Xu:
Joint Client Assignment and UAV Route Planning for Indirect-Communication Federated Learning. CoRR abs/2304.10744 (2023) - [i4]Jieming Bian, Shaolei Ren, Jie Xu:
CAFE: Carbon-Aware Federated Learning in Geographically Distributed Data Centers. CoRR abs/2311.03615 (2023) - [i3]Lei Wang, Jieming Bian, Jie Xu:
Federated Learning with Instance-Dependent Noisy Label. CoRR abs/2312.10324 (2023) - 2022
- [i2]Jieming Bian, Jie Xu:
Mobility Improves the Convergence of Asynchronous Federated Learning. CoRR abs/2206.04742 (2022) - 2021
- [i1]Jieming Bian, Zhu Fu, Jie Xu:
FedSEAL: Semi-Supervised Federated Learning with Self-Ensemble Learning and Negative Learning. CoRR abs/2110.07829 (2021)
Coauthor Index
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