Adaptive Compression in Federated Learning via Side Information
Fuente:
arXiv
Saved in:
| Main Authors: | Isik, Berivan, Pase, Francesco, Gunduz, Deniz, Koyejo, Sanmi, Weissman, Tsachy, Zorzi, Michele |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
BICompFL: Stochastic Federated Learning with Bi-Directional Compression
by: Egger, Maximilian, et al.
Published: (2025)
by: Egger, Maximilian, et al.
Published: (2025)
FedCAda: Adaptive Client-Side Optimization for Accelerated and Stable Federated Learning
by: Zhou, Liuzhi, et al.
Published: (2024)
by: Zhou, Liuzhi, et al.
Published: (2024)
Communication-Efficient Federated Learning through Adaptive Weight Clustering and Server-Side Distillation
by: Tsouvalas, Vasileios, et al.
Published: (2024)
by: Tsouvalas, Vasileios, et al.
Published: (2024)
Mobility Accelerates Learning: Convergence Analysis on Hierarchical Federated Learning in Vehicular Networks
by: Chen, Tan, et al.
Published: (2024)
by: Chen, Tan, et al.
Published: (2024)
Heterogeneity-Aware Cooperative Federated Edge Learning with Adaptive Computation and Communication Compression
by: Zhang, Zhenxiao, et al.
Published: (2024)
by: Zhang, Zhenxiao, et al.
Published: (2024)
Aggressive or Imperceptible, or Both: Network Pruning Assisted Hybrid Byzantines in Federated Learning
by: Ozfatura, Emre, et al.
Published: (2024)
by: Ozfatura, Emre, et al.
Published: (2024)
Adaptive Federated Learning via New Entropy Approach
by: Zheng, Shensheng, et al.
Published: (2023)
by: Zheng, Shensheng, et al.
Published: (2023)
Byzantines can also Learn from History: Fall of Centered Clipping in Federated Learning
by: Ozfatura, Kerem, et al.
Published: (2022)
by: Ozfatura, Kerem, et al.
Published: (2022)
Efficient Model Compression for Hierarchical Federated Learning
by: Zhu, Xi, et al.
Published: (2024)
by: Zhu, Xi, et al.
Published: (2024)
Towards Communication-efficient Federated Learning via Sparse and Aligned Adaptive Optimization
by: Deng, Xiumei, et al.
Published: (2024)
by: Deng, Xiumei, et al.
Published: (2024)
Adaptive Client Selection via Q-Learning-based Whittle Index in Wireless Federated Learning
by: Li, Qiyue, et al.
Published: (2025)
by: Li, Qiyue, et al.
Published: (2025)
Caesar: A Low-deviation Compression Approach for Efficient Federated Learning
by: Yan, Jiaming, et al.
Published: (2024)
by: Yan, Jiaming, et al.
Published: (2024)
Bandwidth-Aware and Overlap-Weighted Compression for Communication-Efficient Federated Learning
by: Tang, Zichen, et al.
Published: (2024)
by: Tang, Zichen, et al.
Published: (2024)
AdaptiveFL: Adaptive Heterogeneous Federated Learning for Resource-Constrained AIoT Systems
by: Jia, Chentao, et al.
Published: (2023)
by: Jia, Chentao, et al.
Published: (2023)
AMSFL: Adaptive Multi-Step Federated Learning via Gradient Difference-Based Error Modeling
by: Xu, Ganglou
Published: (2025)
by: Xu, Ganglou
Published: (2025)
FedAgg: Adaptive Federated Learning with Aggregated Gradients
by: Yuan, Wenhao, et al.
Published: (2023)
by: Yuan, Wenhao, et al.
Published: (2023)
A Joint Approach to Local Updating and Gradient Compression for Efficient Asynchronous Federated Learning
by: Song, Jiajun, et al.
Published: (2024)
by: Song, Jiajun, et al.
Published: (2024)
FedFetch: Faster Federated Learning with Adaptive Downstream Prefetching
by: Yan, Qifan, et al.
Published: (2025)
by: Yan, Qifan, et al.
Published: (2025)
Adaptive Client Selection with Personalization for Communication Efficient Federated Learning
by: de Souza, Allan M., et al.
Published: (2024)
by: de Souza, Allan M., et al.
Published: (2024)
Federated Distillation on Edge Devices: Efficient Client-Side Filtering for Non-IID Data
by: Mujtaba, Ahmed, et al.
Published: (2025)
by: Mujtaba, Ahmed, et al.
Published: (2025)
Personalized Federated Domain-Incremental Learning based on Adaptive Knowledge Matching
by: Li, Yichen, et al.
Published: (2024)
by: Li, Yichen, et al.
Published: (2024)
Accelerating Communication in Deep Learning Recommendation Model Training with Dual-Level Adaptive Lossy Compression
by: Feng, Hao, et al.
Published: (2024)
by: Feng, Hao, et al.
Published: (2024)
Dual-Distilled Heterogeneous Federated Learning with Adaptive Margins for Trainable Global Prototypes
by: Siddika, Fatema, et al.
Published: (2025)
by: Siddika, Fatema, et al.
Published: (2025)
SplitFT: An Adaptive Federated Split Learning System For LLMs Fine-Tuning
by: Shan, Yimeng, et al.
Published: (2026)
by: Shan, Yimeng, et al.
Published: (2026)
FedRIR: Rethinking Information Representation in Federated Learning
by: Huang, Yongqiang, et al.
Published: (2025)
by: Huang, Yongqiang, et al.
Published: (2025)
FedSAE: A Novel Self-Adaptive Federated Learning Framework in Heterogeneous Systems
by: Li, Li, et al.
Published: (2021)
by: Li, Li, et al.
Published: (2021)
Reducing Communication Overhead in Federated Learning for Network Anomaly Detection with Adaptive Client Selection
by: Marfo, William, et al.
Published: (2025)
by: Marfo, William, et al.
Published: (2025)
Benchmarking Mutual Information-based Loss Functions in Federated Learning
by: S, Sarang, et al.
Published: (2025)
by: S, Sarang, et al.
Published: (2025)
An Information-Theoretic Analysis for Federated Learning under Concept Drift
by: Peng, Fu, et al.
Published: (2025)
by: Peng, Fu, et al.
Published: (2025)
Win Fast or Lose Slow: Balancing Speed and Accuracy in Latency-Sensitive Decisions of LLMs
by: Kang, Hao, et al.
Published: (2025)
by: Kang, Hao, et al.
Published: (2025)
Personalized Federated Learning via ADMM with Moreau Envelope
by: Zhu, Shengkun, et al.
Published: (2023)
by: Zhu, Shengkun, et al.
Published: (2023)
pMixFed: Efficient Personalized Federated Learning through Adaptive Layer-Wise Mixup
by: Saadati, Yasaman, et al.
Published: (2025)
by: Saadati, Yasaman, et al.
Published: (2025)
Byzantine-Robust and Communication-Efficient Distributed Learning via Compressed Momentum Filtering
by: Liu, Changxin, et al.
Published: (2024)
by: Liu, Changxin, et al.
Published: (2024)
Adacc: An Adaptive Framework Unifying Compression and Activation Recomputation for LLM Training
by: Chen, Ping, et al.
Published: (2025)
by: Chen, Ping, et al.
Published: (2025)
FedFisher: Leveraging Fisher Information for One-Shot Federated Learning
by: Jhunjhunwala, Divyansh, et al.
Published: (2024)
by: Jhunjhunwala, Divyansh, et al.
Published: (2024)
Accelerating Wireless Distributed Learning via Hybrid Split and Federated Learning Optimization
by: Guo, Kun, et al.
Published: (2025)
by: Guo, Kun, et al.
Published: (2025)
FedAdaVR: Adaptive Variance Reduction for Robust Federated Learning under Limited Client Participation
by: Howlader, S M Ruhul Kabir, et al.
Published: (2026)
by: Howlader, S M Ruhul Kabir, et al.
Published: (2026)
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)
Communication-Efficient Split Learning via Adaptive Feature-Wise Compression
by: Oh, Yongjeong, et al.
Published: (2023)
by: Oh, Yongjeong, et al.
Published: (2023)
FedBAT: Communication-Efficient Federated Learning via Learnable Binarization
by: Li, Shiwei, et al.
Published: (2024)
by: Li, Shiwei, et al.
Published: (2024)
Similar Items
-
BICompFL: Stochastic Federated Learning with Bi-Directional Compression
by: Egger, Maximilian, et al.
Published: (2025) -
FedCAda: Adaptive Client-Side Optimization for Accelerated and Stable Federated Learning
by: Zhou, Liuzhi, et al.
Published: (2024) -
Communication-Efficient Federated Learning through Adaptive Weight Clustering and Server-Side Distillation
by: Tsouvalas, Vasileios, et al.
Published: (2024) -
Mobility Accelerates Learning: Convergence Analysis on Hierarchical Federated Learning in Vehicular Networks
by: Chen, Tan, et al.
Published: (2024) -
Heterogeneity-Aware Cooperative Federated Edge Learning with Adaptive Computation and Communication Compression
by: Zhang, Zhenxiao, et al.
Published: (2024)