Federated Machine Learning

FedML

Federated machine learning is a machine learning setting where multiple entities (clients) collaborate in solving a machine learning problem, while keeping the data decentralized. This setting is particularly useful when the data is sensitive and cannot be shared due to privacy concerns. Federated machine learning algorithms allow the clients to train a global model without sharing their data with each other or with a central server. This approach is used in various applications, such as healthcare, finance, and IoT, where data privacy is a major concern.

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Federated Domain Generalization with Latent Space Inversion Ragja Palakkadavath Hung Le Thanh Nguyen-Tang Svetha Venkatesh Sunil Gupta FedML 60 0 0 11 Dec 2025
Clustered Federated Learning with Hierarchical Knowledge Distillation Sabtain Ahmad Meerzhan Kanatbekova Ivona Brandic Atakan Aral FedML 56 0 0 11 Dec 2025
Fast Factorized Learning: Powered by In-Memory Database Systems Bernhard Stöckl Maximilian E. Schüle FedML 80 0 0 10 Dec 2025
SOFA-FL: Self-Organizing Hierarchical Federated Learning with Adaptive Clustered Data Sharing Yi Ni Xinkun Wang Han Zhang FedML 112 0 0 09 Dec 2025
Minimizing Layerwise Activation Norm Improves Generalization in Federated LearningIEEE Workshop/Winter Conference on Applications of Computer Vision (WACV), 2024 M Yashwanth Gaurav Kumar Nayak Harsh Rangwani Arya Singh R. Venkatesh Babu Anirban Chakraborty FedML 40 0 0 09 Dec 2025
DS FedProxGrad: Asymptotic Stationarity Without Noise Floor in Fair Federated Learning Huzaifa Arif FedML 80 0 0 09 Dec 2025
Fed-SE: Federated Self-Evolution for Privacy-Constrained Multi-Environment LLM Agents Xiang Chen Yuling Shi Qizhen Lan Yuchao Qiu Xiaodong Gu FedML 24 0 0 09 Dec 2025
Machine Learning: Progress and Prospects Alexander Gammerman SSL FedML AI4CE VLM 45 0 0 08 Dec 2025
FedDSR: Federated Deep Supervision and Regularization Towards Autonomous Driving Wei-Bin Kou Guangxu Zhu Bingyang Cheng Chen Zhang Yik-Chung Wu Jianping Wang FedML 28 0 0 07 Dec 2025
Formalisation of Security for Federated Learning with DP and Attacker Advantage in IIIf for Satellite Swarms -- Extended Version Florian Kammüller FedML 16 0 0 06 Dec 2025
Non-Convex Federated Optimization under Cost-Aware Client Selection Xiaowen Jiang Anton Rodomanov Sebastian U. Stich FedML 156 0 0 05 Dec 2025
The MICCAI Federated Tumor Segmentation (FeTS) Challenge 2024: Efficient and Robust Aggregation Methods for Federated Learning Akis Linardos Sarthak Pati Ujjwal Baid Brandon Edwards Patrick Foley ... Leonard L. Klausmann Prashant Shah Bjoern Menze Dimitrios Makris Spyridon Bakas FedML 100 0 0 05 Dec 2025
How Ensemble Learning Balances Accuracy and Overfitting: A Bias-Variance Perspective on Tabular Data Zubair Ahmed Mohammad FedML 20 0 0 05 Dec 2025
Scaling Trust in Quantum Federated Learning: A Multi-Protocol Privacy Design Dev Gurung Shiva Raj Pokhrel FedML 136 0 0 03 Dec 2025
Single-Round Scalable Analytic Federated Learning Alan T. L. Bacellar Mustafa Munir Felipe M. G. França Priscila M. V. Lima Radu Marculescu Lizy K. John FedML 128 0 0 03 Dec 2025
How (Mis)calibrated is Your Federated CLIP and What To Do About It? Mainak Singha Masih Aminbeidokhti Paolo Casari Elisa Ricci Subhankar Roy FedML VLM 109 0 0 03 Dec 2025
A2G-QFL: Adaptive Aggregation with Two Gains in Quantum Federated learning Shanika Iroshi Nanayakkara Shiva Raj Pokhrel FedML 40 0 0 03 Dec 2025
Over-the-Air Federated Learning: Rethinking Edge AI Through Signal Processing Seyed Mohammad Azimi-Abarghouyi Carlo Fischione Kaibin Huang FedML 68 0 0 03 Dec 2025
Differentially Private and Federated Structure Learning in Bayesian Networks Ghita Fassy El Fehri Aurélien Bellet Philippe Bastien FedML 36 0 0 01 Dec 2025
Delta Sum Learning: an approach for fast and global convergence in Gossip Learning Tom Goethals Merlijn Sebrechts Stijn De Schrijver Filip De Turck Bruno Volckaert FedML 48 0 0 01 Dec 2025
Beyond Scaffold: A Unified Spatio-Temporal Gradient Tracking Method Yan Huang Jinming Xu Jiming Chen Karl Henrik Johansson FedML 24 0 0 01 Dec 2025
Topological Federated Clustering via Gravitational Potential Fields under Local Differential Privacy Yunbo Long Jiaquan Zhang Xi Chen Alexandra Brintrup FedML 40 0 0 30 Nov 2025
Cross-Domain Federated Semantic Communication with Global Representation Alignment and Domain-Aware Aggregation Loc X. Nguyen Ji Su Yoon Huy Q. Le Yu Qiao Avi Deb Raha Eui-Nam Huh Walid Saad Dusit Niyato Zhu Han Choong Seon Hong FedML 44 0 0 30 Nov 2025
Operator-Theoretic Framework for Gradient-Free Federated Learning Mohit Kumar Mathias Brucker Alexander Valentinitsch Adnan Husakovic Ali Abbas Manuela Geiß Bernhard A. Moser FedML 88 0 0 30 Nov 2025
Prediction-space knowledge markets for communication-efficient federated learning on multimedia tasks Wenzhang Du FedML 44 0 0 30 Nov 2025
FedSGT: Exact Federated Unlearning via Sequential Group-based Training Bokang Zhang Hong Guan Hong kyu Lee Ruixuan Liu Jia Zou Li Xiong MU FedML 68 0 0 28 Nov 2025
Closing the Generalization Gap in Parameter-efficient Federated Edge Learning Xinnong Du Zhonghao Lyu Xiaowen Cao Chunyang Wen Shuguang Cui Jie Xu FedML 74 0 0 28 Nov 2025
A Trainable Centrality Framework for Modern Data Minh Duc Vu Mingshuo Liu Doudou Zhou FedML 80 0 0 28 Nov 2025
FedRE: A Representation Entanglement Framework for Model-Heterogeneous Federated Learning Yuan Yao Lixu Wang Jiaqi Wu Jin Song Simin Chen Zehua Wang Zijian Tian Wei Chen Huixia Li Xiaoxiao Li FedML 40 0 0 27 Nov 2025
Towards Heterogeneous Quantum Federated Learning: Challenges and Solutions Ratun Rahman Dinh C. Nguyen Christo Kurisummoottil Thomas Walid Saad FedML 145 0 0 27 Nov 2025
A Fast and Flat Federated Learning Method via Weighted Momentum and Sharpness-Aware Minimization Tianle Li Yongzhi Huang Linshan Jiang Chang Liu Qipeng Xie Wenfeng Du Lu Wang Kaishun Wu FedML 141 0 0 27 Nov 2025
FastFHE: Packing-Scalable and Depthwise-Separable CNN Inference Over FHE Wenbo Song Xinxin Fan Quanliang Jing Shaoye Luo Wenqi Wei Chi Lin Yunfeng Lu Ling Liu FedML 28 0 0 27 Nov 2025
Federated Learning Survey: A Multi-Level Taxonomy of Aggregation Techniques, Experimental Insights, and Future Frontiers Meriem Arbaoui Mohamed-el-Amine Brahmia Abdellatif Rahmoun Mourad Zghal FedML 12 0 0 27 Nov 2025
Privacy in Federated Learning with Spiking Neural Networks Dogukan Aksu Jesus Martinez del Rincon Ihsen Alouani AAML FedML 428 0 0 26 Nov 2025
Trustless Federated Learning at Edge-Scale: A Compositional Architecture for Decentralized, Verifiable, and Incentive-Aligned Coordination Pius Onobhayedo Paul Osemudiame Oamen FedML 129 0 0 26 Nov 2025
Privacy-Preserving Federated Vision Transformer Learning Leveraging Lightweight Homomorphic Encryption in Medical AI Al Amin Kamrul Hasan Liang Hong Sharif Ullah MedIm FedML 424 0 0 26 Nov 2025
ParaBlock: Communication-Computation Parallel Block Coordinate Federated Learning for Large Language Models Yujia Wang Yuanpu Cao Jinghui Chen FedML 190 0 0 25 Nov 2025
Stragglers Can Contribute More: Uncertainty-Aware Distillation for Asynchronous Federated Learning Yujia Wang Fenglong Ma Jinghui Chen FedML 197 0 0 25 Nov 2025
Accelerating Wireless Distributed Learning via Hybrid Split and Federated Learning Optimization Kun Guo X. Li Xijun Wang Howard H. Yang W. Feng Tony Q.S. Quek FedML 252 0 0 25 Nov 2025
On the Limits of Momentum in Decentralized and Federated Optimization Riccardo Zaccone Sai Praneeth Karimireddy Carlo Masone FedML 316 0 0 25 Nov 2025
Rethinking Long-tailed Dataset Distillation: A Uni-Level Framework with Unbiased Recovery and Relabeling Xiao Cui Yulei Qin Xinyue Li Wengang Zhou Hongsheng Li Houqiang Li DD FedML 241 0 0 24 Nov 2025
Personalized Federated Segmentation with Shared Feature Aggregation and Boundary-Focused Calibration Ishmam Tashdeed Md. Atiqur Rahman Sabrina Islam Md. Azam Hossain FedML 185 0 0 24 Nov 2025
Merging without Forgetting: Continual Fusion of Task-Specific Models via Optimal Transport Z. Pan Zhikang Chen Ding Li Min Zhang Sen Cui ... Yi Yang Deheng Ye Yu Zhang T. Zhu Tianling Ren MoMe CLL FedML 215 0 0 24 Nov 2025
FedPoisonTTP: A Threat Model and Poisoning Attack for Federated Test-Time Personalization Md Akil Raihan Iftee Syed Md. Ahnaf Hasan Amin Ahsan Ali A. Rahman Sajib Mistry Aneesh Krishna AAML FedML SILM TTA 214 0 0 24 Nov 2025
Mitigating Participation Imbalance Bias in Asynchronous Federated Learning Xiangyu Chang Manyi Yao S. Krishnamurthy Christian Shelton Anirban Chakraborty A. Swami Samet Oymak Amit Roy-Chowdhury FedML 217 0 0 24 Nov 2025
Hi-SAFE: Hierarchical Secure Aggregation for Lightweight Federated Learning Hyeong-Gun Joo Songnam Hong Seunghwan Lee Dong-joon Shin FedML 306 0 0 24 Nov 2025
pFedBBN: A Personalized Federated Test-Time Adaptation with Balanced Batch Normalization for Class-Imbalanced Data Md Akil Raihan Iftee Syed Md. Ahnaf Hasan Mir Sazzat Hossain Rakibul Hasan Rajib Amin Ahsan Ali A. Rahman Sajib Mistry Monowar Bhuyan FedML 199 0 0 22 Nov 2025
Federated Learning Framework for Scalable AI in Heterogeneous HPC and Cloud Environments Sangam Ghimire Paribartan Timalsina Nirjal Bhurtel Bishal Neupane Bigyan Byanju Shrestha Subarna Bhattarai Prajwal Gaire Jessica Thapa Sudan Jha FedML 227 0 0 22 Nov 2025
FIRM: Federated In-client Regularized Multi-objective Alignment for Large Language Models Fatemeh Nourzad Amirhossein Roknilamouki Eylem Ekici Ness B. Shroff FedML 202 0 0 21 Nov 2025
TOFA: Training-Free One-Shot Federated Adaptation for Vision-Language Models Li Zhang Zhongxuan Han Xiaohua Feng Jiaming Zhang Yuyuan Li Linbo Jiang Jianan Lin Chaochao Chen FedML VLM 289 0 0 20 Nov 2025

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