Cover Image

Review of Mathematical Optimization in Federated Learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Yang, Shusen, Zhao, Fangyuan, Zhou, Zihao, Shi, Liang, Ren, Xuebin, Xu, Zongben
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Distributed, Parallel, and Cluster Computing
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

FairGFL: Privacy-Preserving Fairness-Aware Federated Learning with Overlapping Subgraphs
by: Zhou, Zihao, et al.
Published: (2025)

Federated Temporal Graph Clustering
by: Zhou, Zihao, et al.
Published: (2024)

Robust Model Aggregation for Heterogeneous Federated Learning: Analysis and Optimizations
by: Shao, Yumeng, et al.
Published: (2024)

Timely Parameter Updating in Over-the-Air Federated Learning
by: Zhu, Jiaqi, et al.
Published: (2025)

Towards Communication-efficient Federated Learning via Sparse and Aligned Adaptive Optimization
by: Deng, Xiumei, et al.
Published: (2024)

CAFE: Carbon-Aware Federated Learning in Geographically Distributed Data Centers
by: Bian, Jieming, et al.
Published: (2023)

Neighborhood and Global Perturbations Supported SAM in Federated Learning: From Local Tweaks To Global Awareness
by: Li, Boyuan, et al.
Published: (2024)

Ranking-based Client Selection with Imitation Learning for Efficient Federated Learning
by: Tian, Chunlin, et al.
Published: (2024)

Federated Learning Optimization: A Comparative Study of Data and Model Exchange Strategies in Dynamic Networks
by: Luqman, Alka, et al.
Published: (2024)

Accelerating Wireless Distributed Learning via Hybrid Split and Federated Learning Optimization
by: Guo, Kun, et al.
Published: (2025)

EcoLearn: Optimizing the Carbon Footprint of Federated Learning
by: Mehboob, Talha, et al.
Published: (2023)

Federated Learning of Large Language Models with Parameter-Efficient Prompt Tuning and Adaptive Optimization
by: Che, Tianshi, et al.
Published: (2023)

Disentangling data distribution for Federated Learning
by: Zhao, Xinyuan, et al.
Published: (2024)

Collaborative Batch Size Optimization for Federated Learning
by: Geimer, Arno, et al.
Published: (2025)

Federated Learning in the Presence of Adversarial Client Unavailability
by: Su, Lili, et al.
Published: (2023)

Achieving Dimension-Free Communication in Federated Learning via Zeroth-Order Optimization
by: Li, Zhe, et al.
Published: (2024)

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

Emulating Full Participation: An Effective and Fair Client Selection Strategy for Federated Learning
by: Li, Qingming, et al.
Published: (2024)

STHFL: Spatio-Temporal Heterogeneous Federated Learning
by: Guo, Shunxin, et al.
Published: (2025)

FedClust: Optimizing Federated Learning on Non-IID Data through Weight-Driven Client Clustering
by: Islam, Md Sirajul, et al.
Published: (2024)

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

Communication-Efficient Federated Group Distributionally Robust Optimization
by: Guo, Zhishuai, et al.
Published: (2024)

Analytic Personalized Federated Meta-Learning
by: Gu, Shunxian, et al.
Published: (2025)

Federated Model Heterogeneous Matryoshka Representation Learning
by: Yi, Liping, et al.
Published: (2024)

Communication and Computation Efficient Split Federated Learning in O-RAN
by: Gu, Shunxian, et al.
Published: (2025)

SemiSFL: Split Federated Learning on Unlabeled and Non-IID Data
by: Xu, Yang, et al.
Published: (2023)

Optimizing Federated Learning for Scalable Power-demand Forecasting in Microgrids
by: Banerjee, Roopkatha, et al.
Published: (2025)

Vertical Federated Learning Hybrid Local Pre-training
by: Li, Wenguo, et al.
Published: (2024)

Accelerating Hybrid Federated Learning Convergence under Partial Participation
by: Bian, Jieming, et al.
Published: (2023)

Lightweight Federated Learning over Wireless Edge Networks
by: Hou, Xiangwang, et al.
Published: (2025)

A Survey on Contribution Evaluation in Vertical Federated Learning
by: Cui, Yue, et al.
Published: (2024)

Bandwidth-Aware and Overlap-Weighted Compression for Communication-Efficient Federated Learning
by: Tang, Zichen, et al.
Published: (2024)

Optimizing Federated Learning using Remote Embeddings for Graph Neural Networks
by: Naman, Pranjal, et al.
Published: (2025)

FEDBUD: Joint Incentive and Privacy Optimization for Resource-Constrained Federated Learning
by: Liu, Tao, et al.
Published: (2026)

Communication-Efficient Device Scheduling for Federated Learning Using Lyapunov Optimization
by: Perazzone, Jake B., et al.
Published: (2025)

Empowering Federated Learning for Massive Models with NVIDIA FLARE
by: Roth, Holger R., et al.
Published: (2024)

Flexible Clustered Federated Learning for Client-Level Data Distribution Shift
by: Duan, Moming, et al.
Published: (2021)

Unlearning during Learning: An Efficient Federated Machine Unlearning Method
by: Gu, Hanlin, et al.
Published: (2024)

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

Federated Learning with Integrated Sensing, Communication, and Computation: Frameworks and Performance Analysis
by: Liang, Yipeng, et al.
Published: (2024)