FLStore: Efficient Federated Learning Storage for non-training workloads
Fuente:
arXiv
Saved in:
| Main Authors: | Khan, Ahmad Faraz, Fountain, Samuel, Abdelmoniem, Ahmed M., Butt, Ali R., Anwar, Ali |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Towards cost-effective and resource-aware aggregation at Edge for Federated Learning
by: Khan, Ahmad Faraz, et al.
Published: (2022)
by: Khan, Ahmad Faraz, et al.
Published: (2022)
LADs: Leveraging LLMs for AI-Driven DevOps
by: Khan, Ahmad Faraz, et al.
Published: (2025)
by: Khan, Ahmad Faraz, et al.
Published: (2025)
Flashback: Understanding and Mitigating Forgetting in Federated Learning
by: Aljahdali, Mohammed, et al.
Published: (2024)
by: Aljahdali, Mohammed, et al.
Published: (2024)
Task-Agnostic Federation over Decentralized Data: Research Landscape and Visions
by: Wu, Wentai, et al.
Published: (2025)
by: Wu, Wentai, et al.
Published: (2025)
Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters
by: Dongare, Shruti, et al.
Published: (2025)
by: Dongare, Shruti, et al.
Published: (2025)
A Communication and Computation Efficient Fully First-order Method for Decentralized Bilevel Optimization
by: Wen, Min, et al.
Published: (2024)
by: Wen, Min, et al.
Published: (2024)
BLOSSOM: Block-wise Federated Learning Over Shared and Sparse Observed Modalities
by: R, Pranav M, et al.
Published: (2026)
by: R, Pranav M, et al.
Published: (2026)
Fed-Sophia: A Communication-Efficient Second-Order Federated Learning Algorithm
by: Elbakary, Ahmed, et al.
Published: (2024)
by: Elbakary, Ahmed, et al.
Published: (2024)
Empirical Analysis of Asynchronous Federated Learning on Heterogeneous Devices: Efficiency, Fairness, and Privacy Trade-offs
by: Mohammadi, Samaneh, et al.
Published: (2025)
by: Mohammadi, Samaneh, et al.
Published: (2025)
Clustered Federated Learning with Hierarchical Knowledge Distillation
by: Ahmad, Sabtain, et al.
Published: (2025)
by: Ahmad, Sabtain, et al.
Published: (2025)
FedGreen: Carbon-aware Federated Learning with Model Size Adaptation
by: Abbasi, Ali, et al.
Published: (2024)
by: Abbasi, Ali, et al.
Published: (2024)
Efficient Client Selection in Federated Learning
by: Marfo, William, et al.
Published: (2025)
by: Marfo, William, et al.
Published: (2025)
Efficient Federated Finetuning of Tiny Transformers with Resource-Constrained Devices
by: Pfeiffer, Kilian, et al.
Published: (2024)
by: Pfeiffer, Kilian, et al.
Published: (2024)
Efficient Federated Learning with Timely Update Dissemination
by: Jia, Juncheng, et al.
Published: (2025)
by: Jia, Juncheng, et al.
Published: (2025)
Efficient Asynchronous Federated Learning with Sparsification and Quantization
by: Jia, Juncheng, et al.
Published: (2023)
by: Jia, Juncheng, et al.
Published: (2023)
Benchmarking Mutual Information-based Loss Functions in Federated Learning
by: S, Sarang, et al.
Published: (2025)
by: S, Sarang, et al.
Published: (2025)
Learning to Collaborate Over Graphs: A Selective Federated Multi-Task Learning Approach
by: Elbakary, Ahmed, et al.
Published: (2025)
by: Elbakary, Ahmed, et al.
Published: (2025)
Efficient Federated Learning with Heterogeneous Data and Adaptive Dropout
by: Liu, Ji, et al.
Published: (2025)
by: Liu, Ji, et al.
Published: (2025)
The Future of Large Language Model Pre-training is Federated
by: Sani, Lorenzo, et al.
Published: (2024)
by: Sani, Lorenzo, et al.
Published: (2024)
DecHW: Heterogeneous Decentralized Federated Learning Exploiting Second-Order Information
by: Ahmad, Adnan, et al.
Published: (2026)
by: Ahmad, Adnan, et al.
Published: (2026)
LCFed: An Efficient Clustered Federated Learning Framework for Heterogeneous Data
by: Zhang, Yuxin, et al.
Published: (2025)
by: Zhang, Yuxin, et al.
Published: (2025)
TraceFL: Interpretability-Driven Debugging in Federated Learning via Neuron Provenance
by: Gill, Waris, et al.
Published: (2023)
by: Gill, Waris, et al.
Published: (2023)
\mathsf{VISTA}: Decentralized Machine Learning in Adversary Dominated Environments
by: Nodehi, Hanzaleh Akbari, et al.
Published: (2026)
by: Nodehi, Hanzaleh Akbari, et al.
Published: (2026)
SSFL: Discovering Sparse Unified Subnetworks at Initialization for Efficient Federated Learning
by: Ohib, Riyasat, et al.
Published: (2024)
by: Ohib, Riyasat, et al.
Published: (2024)
FedTrans: Efficient Federated Learning via Multi-Model Transformation
by: Zhu, Yuxuan, et al.
Published: (2024)
by: Zhu, Yuxuan, et al.
Published: (2024)
Online Client Scheduling and Resource Allocation for Efficient Federated Edge Learning
by: Gao, Zhidong, et al.
Published: (2024)
by: Gao, Zhidong, et al.
Published: (2024)
An Upload-Efficient Scheme for Transferring Knowledge From a Server-Side Pre-trained Generator to Clients in Heterogeneous Federated Learning
by: Zhang, Jianqing, et al.
Published: (2024)
by: Zhang, Jianqing, et al.
Published: (2024)
Effective Heterogeneous Federated Learning via Efficient Hypernetwork-based Weight Generation
by: Shin, Yujin, et al.
Published: (2024)
by: Shin, Yujin, et al.
Published: (2024)
Communication-Efficient Personalized Federal Graph Learning via Low-Rank Decomposition
by: Liu, Ruyue, et al.
Published: (2024)
by: Liu, Ruyue, et al.
Published: (2024)
SpaFL: Communication-Efficient Federated Learning with Sparse Models and Low computational Overhead
by: Kim, Minsu, et al.
Published: (2024)
by: Kim, Minsu, et al.
Published: (2024)
E-3SFC: Communication-Efficient Federated Learning with Double-way Features Synthesizing
by: Zhou, Yuhao, et al.
Published: (2025)
by: Zhou, Yuhao, et al.
Published: (2025)
Learning Like Humans: Resource-Efficient Federated Fine-Tuning through Cognitive Developmental Stages
by: Wu, Yebo, et al.
Published: (2025)
by: Wu, Yebo, et al.
Published: (2025)
SatFed: A Resource-Efficient LEO Satellite-Assisted Heterogeneous Federated Learning Framework
by: Zhang, Yuxin, et al.
Published: (2024)
by: Zhang, Yuxin, et al.
Published: (2024)
Efficient Federated Learning Using Dynamic Update and Adaptive Pruning with Momentum on Shared Server Data
by: Liu, Ji, et al.
Published: (2024)
by: Liu, Ji, et al.
Published: (2024)
Communication-Efficient Federated Learning for LEO Satellite Networks Integrated with HAPs Using Hybrid NOMA-OFDM
by: Elmahallawy, Mohamed, et al.
Published: (2024)
by: Elmahallawy, Mohamed, et al.
Published: (2024)
When Foresight Pruning Meets Zeroth-Order Optimization: Efficient Federated Learning for Low-Memory Devices
by: Zhang, Pengyu, et al.
Published: (2024)
by: Zhang, Pengyu, et al.
Published: (2024)
Federated Multi-Objective Learning
by: Yang, Haibo, et al.
Published: (2023)
by: Yang, Haibo, et al.
Published: (2023)
Federated Learning with Flexible Architectures
by: Park, Jong-Ik, et al.
Published: (2024)
by: Park, Jong-Ik, et al.
Published: (2024)
Non-Convex Over-the-Air Heterogeneous Federated Learning: A Bias-Variance Trade-off
by: Abrar, Muhammad Faraz Ul, et al.
Published: (2025)
by: Abrar, Muhammad Faraz Ul, et al.
Published: (2025)
On Using Large-Batches in Federated Learning
by: Tyagi, Sahil
Published: (2025)
by: Tyagi, Sahil
Published: (2025)
Similar Items
-
Towards cost-effective and resource-aware aggregation at Edge for Federated Learning
by: Khan, Ahmad Faraz, et al.
Published: (2022) -
LADs: Leveraging LLMs for AI-Driven DevOps
by: Khan, Ahmad Faraz, et al.
Published: (2025) -
Flashback: Understanding and Mitigating Forgetting in Federated Learning
by: Aljahdali, Mohammed, et al.
Published: (2024) -
Task-Agnostic Federation over Decentralized Data: Research Landscape and Visions
by: Wu, Wentai, et al.
Published: (2025) -
Hybrid Learning and Optimization-Based Dynamic Scheduling for DL Workloads on Heterogeneous GPU Clusters
by: Dongare, Shruti, et al.
Published: (2025)