:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Li, Jian, Liu, Yong, Wang, Wei, Wu, Haoran, Wang, Weiping
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Distributed, Parallel, and Cluster Computing
Online Access:	https://arxiv.org/abs/2401.02734
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Sketched Gaussian Mechanism for Private Federated Learning
by: Li, Qiaobo, et al.
Published: (2025)

FedAgg: Adaptive Federated Learning with Aggregated Gradients
by: Yuan, Wenhao, et al.
Published: (2023)

Decentralized Federated Learning with Model Caching on Mobile Agents
by: Wang, Xiaoyu, et al.
Published: (2024)

FedORGP: Guiding Heterogeneous Federated Learning with Orthogonality Regularization on Global Prototypes
by: Guo, Fucheng, et al.
Published: (2025)

FedSR: A Semi-Decentralized Federated Learning Algorithm for Non-IIDness in IoT System
by: Huang, Jianjun, et al.
Published: (2024)

FedBiF: Communication-Efficient Federated Learning via Bits Freezing
by: Li, Shiwei, et al.
Published: (2025)

pFedLoRA: Model-Heterogeneous Personalized Federated Learning with LoRA Tuning
by: Yi, Liping, et al.
Published: (2023)

FedGCS: A Generative Framework for Efficient Client Selection in Federated Learning via Gradient-based Optimization
by: Ning, Zhiyuan, et al.
Published: (2024)

FedSAE: A Novel Self-Adaptive Federated Learning Framework in Heterogeneous Systems
by: Li, Li, et al.
Published: (2021)

Fed-REACT: Federated Representation Learning for Heterogeneous and Evolving Data
by: Chen, Yiyue, et al.
Published: (2025)

FedBAT: Communication-Efficient Federated Learning via Learnable Binarization
by: Li, Shiwei, et al.
Published: (2024)

FedFisher: Leveraging Fisher Information for One-Shot Federated Learning
by: Jhunjhunwala, Divyansh, et al.
Published: (2024)

SketchGuard: Scaling Byzantine-Robust Decentralized Federated Learning via Sketch-Based Screening
by: Rangwala, Murtaza, et al.
Published: (2025)

FedQS: Optimizing Gradient and Model Aggregation for Semi-Asynchronous Federated Learning
by: Li, Yunbo, et al.
Published: (2025)

FedEve: On Bridging the Client Drift and Period Drift for Cross-device Federated Learning
by: Shen, Tao, et al.
Published: (2025)

FedSSA: Semantic Similarity-based Aggregation for Efficient Model-Heterogeneous Personalized Federated Learning
by: Yi, Liping, et al.
Published: (2023)

FedGAT: A Privacy-Preserving Federated Approximation Algorithm for Graph Attention Networks
by: Ambekar, Siddharth, et al.
Published: (2024)

FedHB: Hierarchical Bayesian Federated Learning
by: Kim, Minyoung, et al.
Published: (2023)

FedFetch: Faster Federated Learning with Adaptive Downstream Prefetching
by: Yan, Qifan, et al.
Published: (2025)

FedDD: Toward Communication-efficient Federated Learning with Differential Parameter Dropout
by: Feng, Zhiying, et al.
Published: (2023)

DualFed: Enjoying both Generalization and Personalization in Federated Learning via Hierachical Representations
by: Zhu, Guogang, et al.
Published: (2024)

FedTilt: Towards Multi-Level Fairness-Preserving and Robust Federated Learning
by: Zhang, Binghui, et al.
Published: (2025)

pFedMoE: Data-Level Personalization with Mixture of Experts for Model-Heterogeneous Personalized Federated Learning
by: Yi, Liping, et al.
Published: (2024)

FedGA: A Fair Federated Learning Framework Based on the Gini Coefficient
by: Liu, ShanBin
Published: (2025)

FedReMa: Improving Personalized Federated Learning via Leveraging the Most Relevant Clients
by: Liang, Han, et al.
Published: (2024)

FedOptima: Optimizing Resource Utilization in Federated Learning
by: Zhang, Zihan, et al.
Published: (2025)

FedRIR: Rethinking Information Representation in Federated Learning
by: Huang, Yongqiang, et al.
Published: (2025)

Fed-GAME: Personalized Federated Learning with Graph Attention Mixture-of-Experts For Time-Series Forecasting
by: Li, Yi, et al.
Published: (2026)

FedQueue: Queue-Aware Federated Learning for Cross-Facility HPC Training
by: Li, Yijiang, et al.
Published: (2026)

FedCAda: Adaptive Client-Side Optimization for Accelerated and Stable Federated Learning
by: Zhou, Liuzhi, et al.
Published: (2024)

FedMoE-DA: Federated Mixture of Experts via Domain Aware Fine-grained Aggregation
by: Zhan, Ziwei, et al.
Published: (2024)

FedTeddi: Temporal Drift and Divergence Aware Scheduling for Timely Federated Edge Learning
by: Bai, Yuxuan, et al.
Published: (2025)

FedZero: Leveraging Renewable Excess Energy in Federated Learning
by: Wiesner, Philipp, et al.
Published: (2023)

FedGroup: Efficient Clustered Federated Learning via Decomposed Data-Driven Measure
by: Duan, Moming, et al.
Published: (2020)

FedMSGL: A Self-Expressive Hypergraph Based Federated Multi-View Learning
by: Li, Daoyuan, et al.
Published: (2025)

FedMOA: Federated GRPO for Personalized Reasoning LLMs under Heterogeneous Rewards
by: Wang, Ziyao, et al.
Published: (2026)

FedEx: Expediting Federated Learning over Heterogeneous Mobile Devices by Overlapping and Participant Selection
by: Geng, Jiaxiang, et al.
Published: (2024)

FedQHD: Closed-Form Function-Space Federated Reinforcement Learning
by: Hou, Yuchen, et al.
Published: (2026)

FedOSAA: Improving Federated Learning with One-Step Anderson Acceleration
by: Feng, Xue, et al.
Published: (2025)

FedPref: Federated Learning Across Heterogeneous Multi-objective Preferences
by: Hartmann, Maria, et al.
Published: (2025)