Saved in:
| Main Authors: | Wu, Bibo, Fang, Fang, Wang, Xianbin |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2501.03448 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Stackelberg Game Based Performance Optimization in Digital Twin Assisted Federated Learning over NOMA Networks
by: Wu, Bibo, et al.
Published: (2025)
by: Wu, Bibo, et al.
Published: (2025)
Straggler-Resilient Federated Learning over A Hybrid Conventional and Pinching Antenna Network
by: Wu, Bibo, et al.
Published: (2025)
by: Wu, Bibo, et al.
Published: (2025)
Adaptive UAV-Assisted Hierarchical Federated Learning: Optimizing Energy, Latency, and Resilience for Dynamic Smart IoT
by: Yang, Xiaohong, et al.
Published: (2025)
by: Yang, Xiaohong, et al.
Published: (2025)
Fairness-Constrained Optimization Attack in Federated Learning
by: Kasyap, Harsh, et al.
Published: (2025)
by: Kasyap, Harsh, et al.
Published: (2025)
Rapid and Continuous Trust Evaluation for Effective Task Collaboration Through Siamese Model
by: Zhu, Botao, et al.
Published: (2025)
by: Zhu, Botao, et al.
Published: (2025)
Task-free Adaptive Meta Black-box Optimization
by: Wang, Chao, et al.
Published: (2026)
by: Wang, Chao, et al.
Published: (2026)
Multi-Agent Imitation Learning: Value is Easy, Regret is Hard
by: Tang, Jingwu, et al.
Published: (2024)
by: Tang, Jingwu, et al.
Published: (2024)
Heterogeneity-Aware Personalized Federated Learning for Industrial Predictive Analytics
by: Hu, Yuhan, et al.
Published: (2026)
by: Hu, Yuhan, et al.
Published: (2026)
Data Valuation for Vertical Federated Learning: A Model-free and Privacy-preserving Method
by: Han, Xiao, et al.
Published: (2021)
by: Han, Xiao, et al.
Published: (2021)
Hacking Task Confounder in Meta-Learning
by: Wang, Jingyao, et al.
Published: (2023)
by: Wang, Jingyao, et al.
Published: (2023)
Meta-Learning with Heterogeneous Tasks
by: Si, Zhaofeng, et al.
Published: (2024)
by: Si, Zhaofeng, et al.
Published: (2024)
On Transferring, Merging, and Splitting Task-Oriented Network Digital Twins
by: Zhang, Zifan, et al.
Published: (2025)
by: Zhang, Zifan, et al.
Published: (2025)
Aggregation Alignment for Federated Learning with Mixture-of-Experts under Data Heterogeneity
by: Fang, Zihan, et al.
Published: (2026)
by: Fang, Zihan, et al.
Published: (2026)
Meta-FL: A Novel Meta-Learning Framework for Optimizing Heterogeneous Model Aggregation in Federated Learning
by: Alsulaimawi, Zahir
Published: (2024)
by: Alsulaimawi, Zahir
Published: (2024)
Adaptive Decentralized Federated Learning for Robust Optimization
by: Wu, Shuyuan, et al.
Published: (2025)
by: Wu, Shuyuan, et al.
Published: (2025)
Drift-Aware Federated Learning: A Causal Perspective
by: Fang, Yunjie, et al.
Published: (2025)
by: Fang, Yunjie, et al.
Published: (2025)
Personalized One-shot Federated Graph Learning for Heterogeneous Clients
by: Yan, Guochen, et al.
Published: (2024)
by: Yan, Guochen, et al.
Published: (2024)
Provably Robust Federated Reinforcement Learning
by: Fang, Minghong, et al.
Published: (2025)
by: Fang, Minghong, et al.
Published: (2025)
Federated Online Learning for Heterogeneous Multisource Streaming Data
by: Li, Jingmao, et al.
Published: (2025)
by: Li, Jingmao, et al.
Published: (2025)
Task-Distributionally Robust Data-Free Meta-Learning
by: Hu, Zixuan, et al.
Published: (2023)
by: Hu, Zixuan, et al.
Published: (2023)
TAP: Two-Stage Adaptive Personalization of Multi-Task and Multi-Modal Foundation Models in Federated Learning
by: Lee, Seohyun, et al.
Published: (2025)
by: Lee, Seohyun, et al.
Published: (2025)
Hierarchical Federated Learning with Multi-Timescale Gradient Correction
by: Fang, Wenzhi, et al.
Published: (2024)
by: Fang, Wenzhi, et al.
Published: (2024)
Competitive Advantage Attacks to Decentralized Federated Learning
by: Jia, Yuqi, et al.
Published: (2023)
by: Jia, Yuqi, et al.
Published: (2023)
Social and Physical Attributes-Defined Trust Evaluation for Effective Collaborator Selection in Human-Device Coexistence Systems
by: Zhu, Botao, et al.
Published: (2025)
by: Zhu, Botao, et al.
Published: (2025)
MetaToolAgent: Towards Generalizable Tool Usage in LLMs through Meta-Learning
by: Fang, Zheng, et al.
Published: (2026)
by: Fang, Zheng, et al.
Published: (2026)
HEART: Achieving Timely Multi-Model Training for Vehicle-Edge-Cloud-Integrated Hierarchical Federated Learning
by: Yang, Xiaohong, et al.
Published: (2025)
by: Yang, Xiaohong, et al.
Published: (2025)
Towards Task Sampler Learning for Meta-Learning
by: Wang, Jingyao, et al.
Published: (2023)
by: Wang, Jingyao, et al.
Published: (2023)
Dynamic Clustering for Personalized Federated Learning on Heterogeneous Edge Devices
by: Liu, Heting, et al.
Published: (2025)
by: Liu, Heting, et al.
Published: (2025)
UAV-Assisted Multi-Task Federated Learning with Task Knowledge Sharing
by: Yang, Yubo, et al.
Published: (2025)
by: Yang, Yubo, et al.
Published: (2025)
System Prompt Optimization with Meta-Learning
by: Choi, Yumin, et al.
Published: (2025)
by: Choi, Yumin, et al.
Published: (2025)
Towards Seamless Hierarchical Federated Learning under Intermittent Client Participation: A Stagewise Decision-Making Methodology
by: Wu, Minghong, et al.
Published: (2025)
by: Wu, Minghong, et al.
Published: (2025)
MAESTRO: Meta-learning Adaptive Estimation of Scalarization Trade-offs for Reward Optimization
by: Zhao, Yang, et al.
Published: (2026)
by: Zhao, Yang, et al.
Published: (2026)
FedOne: Query-Efficient Federated Learning for Black-box Discrete Prompt Learning
by: Wang, Ganyu, et al.
Published: (2025)
by: Wang, Ganyu, et al.
Published: (2025)
Few-Shot Learning for Dynamic Operations of Automated Electric Taxi Fleets under Evolving Charging Infrastructure: A Meta-Deep Reinforcement Learning Approach
by: Li, Xiaozhuang, et al.
Published: (2026)
by: Li, Xiaozhuang, et al.
Published: (2026)
Goal-Oriented Influence-Maximizing Data Acquisition for Learning and Optimization
by: Yao, Weichi, et al.
Published: (2026)
by: Yao, Weichi, et al.
Published: (2026)
A Two-Stage Federated Learning Approach for Industrial Prognostics Using Large-Scale High-Dimensional Signals
by: Su, Yuqi, et al.
Published: (2024)
by: Su, Yuqi, et al.
Published: (2024)
Learning to Learn with Contrastive Meta-Objective
by: Wu, Shiguang, et al.
Published: (2024)
by: Wu, Shiguang, et al.
Published: (2024)
Heterogeneous Tasks Offloading in Vehicular Edge Computing: A Federated Meta Deep Reinforcement Learning Approach
by: Huang, Yaorong, et al.
Published: (2026)
by: Huang, Yaorong, et al.
Published: (2026)
Find a Scapegoat: Poisoning Membership Inference Attack and Defense to Federated Learning
by: Mo, Wenjin, et al.
Published: (2025)
by: Mo, Wenjin, et al.
Published: (2025)
CO-PFL: Contribution-Oriented Personalized Federated Learning for Heterogeneous Networks
by: Xing, Ke, et al.
Published: (2025)
by: Xing, Ke, et al.
Published: (2025)
Similar Items
-
Stackelberg Game Based Performance Optimization in Digital Twin Assisted Federated Learning over NOMA Networks
by: Wu, Bibo, et al.
Published: (2025) -
Straggler-Resilient Federated Learning over A Hybrid Conventional and Pinching Antenna Network
by: Wu, Bibo, et al.
Published: (2025) -
Adaptive UAV-Assisted Hierarchical Federated Learning: Optimizing Energy, Latency, and Resilience for Dynamic Smart IoT
by: Yang, Xiaohong, et al.
Published: (2025) -
Fairness-Constrained Optimization Attack in Federated Learning
by: Kasyap, Harsh, et al.
Published: (2025) -
Rapid and Continuous Trust Evaluation for Effective Task Collaboration Through Siamese Model
by: Zhu, Botao, et al.
Published: (2025)