v1v2 (latest)

FedBalancer: Data and Pace Control for Efficient Federated Learning on Heterogeneous Clients

ACM SIGMOBILE International Conference on Mobile Systems, Applications, and Services (MobiSys), 2022

5 January 2022

Papers citing "FedBalancer: Data and Pace Control for Efficient Federated Learning on Heterogeneous Clients"

37 / 37 papers shown

Toward Storage-Aware Learning with Compressed Data An Empirical Exploratory Study on JPEG

166

24 Dec 2025

Improving Local Training in Federated Learning via Temperature Scaling

JeongGil Ko

254

24 Dec 2025

Federated Learning Framework for Scalable AI in Heterogeneous HPC and Cloud Environments

Bigyan Byanju Shrestha

327

22 Nov 2025

FedHybrid: Breaking the Memory Wall of Federated Learning via Hybrid Tensor ManagementACM International Conference on Embedded Networked Sensor Systems (SenSys), 2024

218

13 Oct 2025

FLAMMABLE: A Multi-Model Federated Learning Framework with Multi-Model Engagement and Adaptive Batch Sizes

12 Oct 2025

PQFed: A Privacy-Preserving Quality-Controlled Federated Learning Framework

131

25 Sep 2025

PracMHBench: Re-evaluating Model-Heterogeneous Federated Learning Based on Practical Edge Device ConstraintsDesign Automation Conference (DAC), 2025

224

04 Sep 2025

HSplitLoRA: A Heterogeneous Split Parameter-Efficient Fine-Tuning Framework for Large Language Models

419

05 May 2025

Moss: Proxy Model-based Full-Weight Aggregation in Federated Learning with Heterogeneous ModelsProceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies (IMWUT), 2025

497

13 Mar 2025

Smoothing ADMM for Non-convex and Non-smooth Hierarchical Federated Learning

Reza Mirzaeifard

Stefan Werner

FedML

232

13 Mar 2025

FedConv: A Learning-on-Model Paradigm for Heterogeneous Federated ClientsACM SIGMOBILE International Conference on Mobile Systems, Applications, and Services (MobiSys), 2024

576

28 Feb 2025

(FL)$^2$: Overcoming Few Labels in Federated Semi-Supervised Learning

(FL)

^2

: Overcoming Few Labels in Federated Semi-Supervised LearningNeural Information Processing Systems (NeurIPS), 2024

374

30 Oct 2024

Delta: A Cloud-assisted Data Enrichment Framework for On-Device Continual LearningACM/IEEE International Conference on Mobile Computing and Networking (MobiCom), 2024

368

24 Oct 2024

Breaking the Memory Wall for Heterogeneous Federated Learning via Model SplittingIEEE Transactions on Parallel and Distributed Systems (TPDS), 2024

253

12 Oct 2024

ParallelSFL: A Novel Split Federated Learning Framework Tackling Heterogeneity IssuesACM/IEEE International Conference on Mobile Computing and Networking (MobiCom), 2024

Liusheng Huang

297

02 Oct 2024

FIARSE: Model-Heterogeneous Federated Learning via Importance-Aware Submodel ExtractionNeural Information Processing Systems (NeurIPS), 2024

Tianci Liu

Jing Gao

326

28 Jul 2024

FedEx: Expediting Federated Learning over Heterogeneous Mobile Devices by Overlapping and Participant Selection

451

01 Jul 2024

Agent-oriented Joint Decision Support for Data Owners in Auction-based Federated LearningIEEE International Conference on Multimedia and Expo (ICME), 2024

119

09 May 2024

LIFL: A Lightweight, Event-driven Serverless Platform for Federated LearningConference on Machine Learning and Systems (MLSys), 2024

Shixiong Qi

K. K. Ramakrishnan

Myungjin Lee

325

05 May 2024

Automated Federated Pipeline for Parameter-Efficient Fine-Tuning of Large Language Models

Yuguang Fang

276

09 Apr 2024

Not All Federated Learning Algorithms Are Created Equal: A Performance Evaluation Study

Ali Payani

173

26 Mar 2024

A Comprehensive Survey of Federated Transfer Learning: Challenges, Methods and Applications

310

03 Mar 2024

Knowledge Rumination for Client Utility Evaluation in Heterogeneous Federated Learning

143

16 Dec 2023

MergeSFL: Split Federated Learning with Feature Merging and Batch Size RegulationIEEE International Conference on Data Engineering (ICDE), 2023

342

22 Nov 2023

FedTherapist: Mental Health Monitoring with User-Generated Linguistic Expressions on Smartphones via Federated LearningConference on Empirical Methods in Natural Language Processing (EMNLP), 2023

245

25 Oct 2023

DYNAMITE: Dynamic Interplay of Mini-Batch Size and Aggregation Frequency for Federated Learning with Static and Streaming Dataset

Xu Chen

269

20 Oct 2023

Mitigating Group Bias in Federated Learning for Heterogeneous DevicesConference on Fairness, Accountability and Transparency (FAccT), 2023

341

13 Sep 2023

FwdLLM: Efficient FedLLM using Forward Gradient

Mengwei Xu

267

26 Aug 2023

Federated Learning in IoT: a Survey from a Resource-Constrained Perspective

Ishmeet Kaur

232

25 Aug 2023

DynamicFL: Balancing Communication Dynamics and Client Manipulation for Federated LearningAnnual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks (SECON), 2023

Bocheng Chen

Nikolay Ivanov

Guangjing Wang

Qiben Yan

211

16 Jul 2023

Flame: Simplifying Topology Extension in Federated LearningACM Symposium on Cloud Computing (SoCC), 2023

292

09 May 2023

FS-Real: Towards Real-World Cross-Device Federated LearningKnowledge Discovery and Data Mining (KDD), 2023

Jingren Zhou

291

23 Mar 2023

Recent Advances on Federated Learning: A Systematic SurveyNeurocomputing (Neurocomputing), 2023

256

177

03 Jan 2023

Federated Few-Shot Learning for Mobile NLPACM/IEEE International Conference on Mobile Computing and Networking (MobiCom), 2022

Mengwei Xu

284

12 Dec 2022

Client Selection in Federated Learning: Principles, Challenges, and OpportunitiesIEEE Internet of Things Journal (IEEE IoT J.), 2022

341

235

03 Nov 2022

To Store or Not? Online Data Selection for Federated Learning with Limited StorageThe Web Conference (WWW), 2022

489

01 Sep 2022

FedAdapter: Efficient Federated Learning for Modern NLP

Mengwei Xu

249

20 May 2022