Reviving Stale Updates: Data-Free Knowledge Distillation for Asynchronous Federated Learning
Fuente:
arXiv
Saved in:
| Main Authors: | Askin, Baris, Roth, Holger R., Sun, Zhenyu, Joe-Wong, Carlee, Joshi, Gauri, Xu, Ziyue |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
FedAST: Federated Asynchronous Simultaneous Training
by: Askin, Baris, et al.
Published: (2024)
by: Askin, Baris, et al.
Published: (2024)
Federated Communication-Efficient Multi-Objective Optimization
by: Askin, Baris, et al.
Published: (2024)
by: Askin, Baris, et al.
Published: (2024)
PubSwap: Public-Data Off-Policy Coordination for Federated RLVR
by: Nayak, Anupam, et al.
Published: (2026)
by: Nayak, Anupam, et al.
Published: (2026)
Federate the Router: Learning Language Model Routers with Sparse and Decentralized Evaluations
by: Askin, Baris, et al.
Published: (2026)
by: Askin, Baris, et al.
Published: (2026)
Internal Planning in Language Models: Characterizing Horizon and Branch Awareness
by: Ustaomeroglu, Muhammed, et al.
Published: (2025)
by: Ustaomeroglu, Muhammed, et al.
Published: (2025)
Emergent and Subliminal Misalignment Through the Lens of Data-Mediated Transfer
by: Askin, Baris, et al.
Published: (2026)
by: Askin, Baris, et al.
Published: (2026)
Ravan: Multi-Head Low-Rank Adaptation for Federated Fine-Tuning
by: Raje, Arian, et al.
Published: (2025)
by: Raje, Arian, et al.
Published: (2025)
FedTLU: Federated Learning with Targeted Layer Updates
by: Park, Jong-Ik, et al.
Published: (2024)
by: Park, Jong-Ik, et al.
Published: (2024)
Degree of Staleness-Aware Data Updating in Federated Learning
by: Liu, Tao, et al.
Published: (2025)
by: Liu, Tao, et al.
Published: (2025)
FedPSA: Modeling Behavioral Staleness in Asynchronous Federated Learning
by: Lu, Chaoyi, et al.
Published: (2026)
by: Lu, Chaoyi, et al.
Published: (2026)
Federated Learning with Flexible Architectures
by: Park, Jong-Ik, et al.
Published: (2024)
by: Park, Jong-Ik, et al.
Published: (2024)
FedStaleWeight: Buffered Asynchronous Federated Learning with Fair Aggregation via Staleness Reweighting
by: Ma, Jeffrey, et al.
Published: (2024)
by: Ma, Jeffrey, et al.
Published: (2024)
Optimizing Asynchronous Federated Learning: A Delicate Trade-Off Between Model-Parameter Staleness and Update Frequency
by: Alahyane, Abdelkrim, et al.
Published: (2025)
by: Alahyane, Abdelkrim, et al.
Published: (2025)
FedSPD: A Soft-clustering Approach for Personalized Decentralized Federated Learning
by: Lin, I-Cheng, et al.
Published: (2024)
by: Lin, I-Cheng, et al.
Published: (2024)
Memory-Based Advantage Shaping for LLM-Guided Reinforcement Learning
by: Nourzad, Narjes, et al.
Published: (2026)
by: Nourzad, Narjes, et al.
Published: (2026)
Revisiting Gradient Staleness: Evaluating Distance Metrics for Asynchronous Federated Learning Aggregation
by: Wilhelm, Patrick, et al.
Published: (2026)
by: Wilhelm, Patrick, et al.
Published: (2026)
MIRA: Memory-Integrated Reinforcement Learning Agent with Limited LLM Guidance
by: Nourzad, Narjes, et al.
Published: (2026)
by: Nourzad, Narjes, et al.
Published: (2026)
Debiasing Federated Learning with Correlated Client Participation
by: Sun, Zhenyu, et al.
Published: (2024)
by: Sun, Zhenyu, et al.
Published: (2024)
Neural Combinatorial Clustered Bandits for Recommendation Systems
by: Atalar, Baran, et al.
Published: (2024)
by: Atalar, Baran, et al.
Published: (2024)
M3Net: A Multi-Metric Mixture of Experts Network Digital Twin with Graph Neural Networks
by: Guda, Blessed, et al.
Published: (2025)
by: Guda, Blessed, et al.
Published: (2025)
Adversarial Robustness Unhardening via Backdoor Attacks in Federated Learning
by: Kim, Taejin, et al.
Published: (2023)
by: Kim, Taejin, et al.
Published: (2023)
Matrix-Space Reinforcement Learning for Reusing Local Transition Geometry
by: Zhang, Zuyuan, et al.
Published: (2026)
by: Zhang, Zuyuan, et al.
Published: (2026)
Efficient Federated Learning against Heterogeneous and Non-stationary Client Unavailability
by: Xiang, Ming, et al.
Published: (2024)
by: Xiang, Ming, et al.
Published: (2024)
Adaptive Federated Learning via Dynamical System Model
by: Agarwal, Aayushya, et al.
Published: (2025)
by: Agarwal, Aayushya, et al.
Published: (2025)
FedGAT: A Privacy-Preserving Federated Approximation Algorithm for Graph Attention Networks
by: Ambekar, Siddharth, et al.
Published: (2024)
by: Ambekar, Siddharth, et al.
Published: (2024)
Empowering Federated Learning with Implicit Gossiping: Mitigating Connection Unreliability Amidst Unknown and Arbitrary Dynamics
by: Xiang, Ming, et al.
Published: (2024)
by: Xiang, Ming, et al.
Published: (2024)
FedECADO: A Dynamical System Model of Federated Learning
by: Agarwal, Aayushya, et al.
Published: (2024)
by: Agarwal, Aayushya, et al.
Published: (2024)
Pairwise Elimination with Instance-Dependent Guarantees for Bandits with Cost Subsidy
by: Juneja, Ishank, et al.
Published: (2025)
by: Juneja, Ishank, et al.
Published: (2025)
DYNAMITE: Dynamic Interplay of Mini-Batch Size and Aggregation Frequency for Federated Learning with Static and Streaming Dataset
by: Liu, Weijie, et al.
Published: (2023)
by: Liu, Weijie, et al.
Published: (2023)
Initialization Matters: Unraveling the Impact of Pre-Training on Federated Learning
by: Jhunjhunwala, Divyansh, et al.
Published: (2025)
by: Jhunjhunwala, Divyansh, et al.
Published: (2025)
HumekaFL: Automated Detection of Neonatal Asphyxia Using Federated Learning
by: Zantou, Pamely, et al.
Published: (2024)
by: Zantou, Pamely, et al.
Published: (2024)
FedBaF: Federated Learning Aggregation Biased by a Foundation Model
by: Park, Jong-Ik, et al.
Published: (2024)
by: Park, Jong-Ik, et al.
Published: (2024)
Tackling Intertwined Data and Device Heterogeneities in Federated Learning with Unlimited Staleness
by: Wang, Haoming, et al.
Published: (2023)
by: Wang, Haoming, et al.
Published: (2023)
FedFisher: Leveraging Fisher Information for One-Shot Federated Learning
by: Jhunjhunwala, Divyansh, et al.
Published: (2024)
by: Jhunjhunwala, Divyansh, et al.
Published: (2024)
Neural Bandit Based Optimal LLM Selection for a Pipeline of Subtasks
by: Atalar, Baran, et al.
Published: (2025)
by: Atalar, Baran, et al.
Published: (2025)
Cost-Ordered Feasibility for Multi-Armed Bandits with Cost Subsidy
by: Juneja, Ishank, et al.
Published: (2026)
by: Juneja, Ishank, et al.
Published: (2026)
Mitigating Staleness in Asynchronous Pipeline Parallelism via Basis Rotation
by: Jung, Hyunji, et al.
Published: (2026)
by: Jung, Hyunji, et al.
Published: (2026)
An LLM-Based Digital Twin for Optimizing Human-in-the Loop Systems
by: Yang, Hanqing, et al.
Published: (2024)
by: Yang, Hanqing, et al.
Published: (2024)
FLAMMABLE: A Multi-Model Federated Learning Framework with Multi-Model Engagement and Adaptive Batch Sizes
by: Lin, Shouxu, et al.
Published: (2025)
by: Lin, Shouxu, et al.
Published: (2025)
Intelligent Communication Planning for Constrained Environmental IoT Sensing with Reinforcement Learning
by: Hu, Yi, et al.
Published: (2023)
by: Hu, Yi, et al.
Published: (2023)
Similar Items
-
FedAST: Federated Asynchronous Simultaneous Training
by: Askin, Baris, et al.
Published: (2024) -
Federated Communication-Efficient Multi-Objective Optimization
by: Askin, Baris, et al.
Published: (2024) -
PubSwap: Public-Data Off-Policy Coordination for Federated RLVR
by: Nayak, Anupam, et al.
Published: (2026) -
Federate the Router: Learning Language Model Routers with Sparse and Decentralized Evaluations
by: Askin, Baris, et al.
Published: (2026) -
Internal Planning in Language Models: Characterizing Horizon and Branch Awareness
by: Ustaomeroglu, Muhammed, et al.
Published: (2025)