A decentralized federated learning architecture is proposed to apply to the Businesses-to-Businesses scenarios by introducing the consortium blockchain in this paper. We introduce a model verification mechanism to ensure the quality of local models trained by participators. To analyze the latency of the system, a latency model is constructed by considering the work flow of the architecture. Finally the experiment results show that our latency model does well in quantifying the actual delays.
A Distributed Computation Model Based on Federated Learning Integrates Heterogeneous models and Consortium Blockchain for Solving Time-Varying Problems
University of Macau（澳门大学）；Chinese University of Hong Kong, Shenzhen（香港中文大学（深圳））；Shenzhen Institute of Artificial Intelligence and Robotics for Society（深圳人工智能与机器人研究院）；Northwestern Polytechnical University（西北工业大学）
Federated Learning with Multi-Partner OneFlorida+ Consortium Data for Predicting Major Postoperative Complications
Intelligent Clinical Care Center, University of Florida（佛罗里达大学智能临床护理中心）；Department of Medicine, Division of Nephrology, Hypertension, and Renal Transplantation, University of Florida（佛罗里达大学医学系肾病、高血压和肾移植分部）；Department of Surgery, University of Florida（佛罗里达大学外科系）；Department of Biomedical Engineering, University of Florida（佛罗里达大学生物医学工程系）
Quantum Cloud and Distributed Systems (qCLOUDS) Lab, School of Computing and Information Systems, The University of Melbourne, Australia（量子云与分布式系统实验室，计算机与信息系统学院，墨尔本大学，澳大利亚）；Department of Computer Science and Engineering, University of Visvesvaraya College of Engineering, Bangalore University, India（计算机科学与工程系，维萨瓦拉亚工程学院，班加罗尔大学，印度）
Development and Design of FLKit: A Structured Onboarding Toolkit for Federated Learning in Health and Life Sciences
STADIUS, Department of Electrical Engineering (ESAT), KU Leuven（STADIUS部门，电气工程系（ESAT），鲁汶大学）；Biomedical Research Institute (BIOMED), Hasselt University（生物医学研究所（BIOMED），哈塞尔特大学）；Data Science Institute (DSI), Hasselt University（数据科学研究所（DSI），哈塞尔特大学）；Department of Medical Genetics, University of Antwerp（医学遗传学系，安特卫普大学）
Multi-Modal Dataset Creation for Federated Learning with DICOM Structured Reports
DZHK (German Centre for Cardiovascular Research, all partner sites)（德国心血管研究中心（所有合作站点））；Heidelberg University Hospital（海德堡大学医院）；Informatics for Life Institute（生命信息学研究所）；University Medical Center Hamburg-Eppendorf（汉堡埃彭多夫大学医学中心）；University Hospital Münster（明斯特大学医院）
