Federated Learning Platform

Federated learning platforms aim to enable collaborative machine learning across decentralized datasets, preserving data privacy while improving model performance. Current research emphasizes addressing heterogeneity in data, models, and computational resources, exploring techniques like hierarchical personalized models, ensemble learning, and flexible, plug-and-play architectures to enhance efficiency and robustness. These platforms are crucial for applications like brain-computer interfaces and mobile robotics, where data sharing is limited, and offer a standardized approach to facilitate broader adoption of federated learning across diverse scientific domains and industrial settings.

Papers

October 2, 2024

A Federated Learning Platform as a Service for Advancing Stroke Management in European Clinical Centers
Diogo Reis Santos, Albert Sund Aillet, Antonio Boiano, Usevalad Milasheuski, Lorenzo Giusti, Marco Di Gennaro, Sanaz Kianoush, Luca Barbieri, Monica Nicoli, Michele Carminati, Alessandro E. C. Redondi, Stefano Savazzi, Luigi Serio
Machine Learning Machine Learning Model Federated Learning Service Provider Healthcare Data Multi Center Stroke Patient Federated Learning Platform

August 14, 2023

Aggregating Intrinsic Information to Enhance BCI Performance through Federated Learning
Rui Liu, Yuanyuan Chen, Anran Li, Yi Ding, Han Yu, Cuntai Guan
Brain Computer Interface EEG Data Motor Imagery EEG Datasets Brain Computer Interface Performance Intrinsic Class Federated Learning Platform

July 5, 2023

Towards Open Federated Learning Platforms: Survey and Vision from Technical and Legal Perspectives
Moming Duan, Qinbin Li, Linshan Jiang, Bingsheng He
Timely Survey Federated Learning Vision Paper Technical Report Indirect Reciprocity Legal Article Open Source Federated Learning Framework Federated Learning Platform Decentralized Cooperation

May 4, 2023

Federated Ensemble-Directed Offline Reinforcement Learning
Desik Rengarajan, Nitin Ragothaman, Dileep Kalathil, Srinivas Shakkottai
Offline Reinforcement Learning Federated Prompt Cooperation Federated Offline Reinforcement Learning Federated Learning Platform

July 21, 2022

UniFed: All-In-One Federated Learning Platform to Unify Open-Source Frameworks
Xiaoyuan Liu, Tianneng Shi, Chulin Xie, Qinbin Li, Kangping Hu, Haoyu Kim, Xiaojun Xu, The-Anh Vu-Le, Zhen Huang, Arash Nourian, Bo Li, Dawn Song
Federated Learning Open Source Framework Open Source Federated Learning Framework Federated Learning Platform

June 21, 2022

WrapperFL: A Model Agnostic Plug-in for Industrial Federated Learning
Xueyang Wu, Shengqi Tan, Qian Xu, Qiang Yang
Federated Learning Ensemble Learning Privacy Preserving Heterogeneous Model Generic Plugin Federated Learning Platform

April 11, 2022

FederatedScope: A Flexible Federated Learning Platform for Heterogeneity
Yuexiang Xie, Zhen Wang, Dawei Gao, Daoyuan Chen, Liuyi Yao, Weirui Kuang, Yaliang Li, Bolin Ding, Jingren Zhou
Federated Learning Federated Setting Event Based Asynchronous Training Federated Learning Platform