This work presents a use case of federated learning (FL) applied to discovering a maze with LiDAR sensors-equipped robots. Goal here is to train classification models to accurately identify the shapes of grid areas within two different square mazes made up with irregular shaped walls. Due to the use of different shapes for the walls, a classification model trained in one maze that captures its structure does not generalize for the other. This issue is resolved by adopting FL framework between the robots that explore only one maze so that the collective knowledge allows them to operate accurately in the unseen maze. This illustrates the effectiveness of FL in real-world applications in terms of enhancing classification accuracy and robustness in maze discovery tasks.
Industry-Scale Orchestrated Federated Learning for Drug Discovery
Amgen（安进公司）
为了将联邦学习应用于药物发现，我们在欧洲创新药物计划（IMI）项目MELLODDY（授权编号831472）的背景下开发了一个新平台，该项目由10家制药公司，学术研究实验室，大型工业公司和初创公司组成。MELLODDY平台是第一个能够创建全球药物发现联合模型的行业级平台，而无需共享各个合作伙伴的机密数据集。在每次训练迭代之后，通过以加密、安全的方式聚合所有贡献伙伴的梯度，在平台上训练联合模型。该平台部署在Amazon Web Services（AWS）多帐户架构上，在私有网络中运行Kubernetes集群。在组织上，不同合作伙伴的作用被编入平台上的不同权利和许可，并以分散的方式进行管理。MELLODDY平台产生了新的科学发现，这些发现在一篇配套论文中进行了描述。
Accurate and Private Diagnosis of Rare Genetic Syndromes from Facial Images with Federated Deep Learning
Medical Data Privacy and Privacy Preserving Machine Learning (MDPPML)（医学数据隐私与隐私保护机器学习）；University of Tübingen（图宾根大学）；Institute for Bioinformatics and Medical Informatics (IBMI)（生物信息学与医学信息学研究所）；Institute for Genomic Statistics and Bioinformatics（基因组统计与生物信息学研究所）；University of Bonn（波恩大学）
A Survey of Trustworthy Federated Learning with Perspectives on Security, Robustness, and Privacy
The Chinese University of Hong Kong（香港中文大学）；University of Electronic Science and Technology of China（电子科技大学）；Peng Cheng Lab（鹏城实验室）；Harbin Institute of Technology, Shenzhen（哈尔滨工业大学（深圳））
Multi-center Medical Data Mining with FL-Net - A One-stop Shop for Federated Learning
University of Hamburg（汉堡大学）；Sapienza University of Rome（罗马第一大学）；University of Campania Luigi Vanvitelli（坎帕尼亚大学路易吉·万维泰利）；Semmelweis University（塞麦尔维斯大学）；SC Egnosis SRL（SC Egnosis公司）；UCL Queen Square Institute of Neurology（伦敦大学学院皇后广场神经学研究所）；LMU München（慕尼黑大学）；LMU Hospital（慕尼黑大学医院）；Research Institute – Digital Human Rights Center（数字人权中心研究所）；Medical University of Vienna（维也纳医科大学）；SBA Research gGmbH（SBA研究中心）；Joslin Diabetes Center（乔斯林糖尿病中心）；Harvard Medical School（哈佛医学院）；Karolinska Institutet（卡罗林斯卡学院）；Södersjukhuset（南斯德哥尔摩综合医院）；University College Cork（科克大学学院）；Karolinska University Hospital（卡罗林斯卡大学医院）；Mass General Brigham（麻省总布里格姆医院）；University of Southern Denmark（南丹麦大学）；Université Paris-Saclay（巴黎-萨克雷大学）；INRAE（法国国家农业、食品与环境研究院）
Label-shift robust federated feature screening for high-dimensional classification
Center for Applied Statistics and School of Statistics Renmin University of China（应用统计中心和中国人民大学统计学院）；School of Mathematics and Statistics Xi’an Jiaotong University（西安交通大学数学与统计学院）；Department of Mathematics and Fundamental Research Peng Cheng Laboratory School of Mathematics and Statistics Xi’an Jiaotong University（数学与基础研究部鹏城实验室数学与统计学院）
$f$-FUM: Federated Unlearning via min--max and $f$-divergence
Department of Statistics, Universite de Geneve, Geneva, Switzerland（日内瓦大学统计系）；University of Cambridge, Cambridge, United Kingdom（剑桥大学）；The Alan Turing Institute, London, UK（艾伦·图灵研究所）
A new type of federated clustering: A non-model-sharing approach
Center for Artificial Intelligence Research（人工智能研究中心）；Tsukuba Institute for Advanced Research（茨口高级研究机构）；University of Tsukuba（茨口大学）；Graduate School of Science and Technology（科学与技术研究生院）；Institute of Systems and Information Engineering（系统与信息工程研究所）
Federated Learning in Chemical Engineering: A Tutorial on a Framework for Privacy-Preserving Collaboration Across Distributed Data Sources
SVKM's Dwarkadas J. Sanghvi College of Engineering（SVKM's 德瓦卡达斯·J.桑格维工程学院）；Davidson School of Chemical Engineering, Purdue University（普渡大学戴维森化学工程学院）；Federal University of Rio de Janeiro（里约热内卢联邦大学）
Federated Causal Discovery from Heterogeneous Data
Mohamed bin Zayed University of Artificial Intelligence（穆罕默德·本·扎耶德人工智能大学）；Carnegie Mellon University（卡内基梅隆大学）；University of California San Diego（加利福尼亚大学圣迭戈分校）
FedLoGe: Joint Local and Generic Federated Learning under Long-tailed Data
University of Electronic Science and Technology of China（电子科技大学）；Angelalign Technology Inc（时代天使科技有限公司）；Zhejiang University（浙江大学）；IHPC, Agency for Science, Technology and Research, Singapore（新加坡科技研究局信息通信研究院）；CFAR, Agency for Science, Technology and Research, Singapore（新加坡科技研究局计算科学与工程中心）；Singapore University of Technology and Design（新加坡科技设计大学）
McGill University（麦吉尔大学）；ETH Zürich（苏黎世联邦理工学院）；GlaxoSmithKline（葛兰素史克）；TU Munich（慕尼黑工业大学）；Helmholtz AI（亥姆霍兹人工智能研究所）；Max Planck Institute for Intelligent Systems（马克斯·普朗克智能系统研究所）
Generalized Category Discovery in Federated Graph Learning
Shandong University, School of Airspace Science and Engineering（山东大学，空天学院）；Beijing Institute of Technology, School of Computer Science and Technology（北京理工大学，计算机科学与技术学院）
Differential Privacy-Driven Framework for Enhancing Heart Disease Prediction
School of Computer Science and Technology（计算机科学与技术学院）；Algoma University（阿尔戈马大学）；School of Electrical Engineering and Computer Science（电气工程与计算机科学学院）；University of Ottawa（渥太华大学）
High-Energy Concentration for Federated Learning in Frequency Domain
State Key Laboratory of Integrated Services Networks, Xidian University（信息服务网络国家重点实验室，西安电子科技大学）；College of Electrical and Information Engineering, Hunan University（湖南大学电气与信息工程学院）
A Survey on Federated Causal Discovery and Inference
School of Computer Science, Nanjing University of Posts and Telecommunications（南京邮电大学计算机学院）；School of Computer Science and Information Engineering, Hefei University of Technology（合肥工业大学计算机与信息工程学院）；College of Computing and Data Science, Nanyang Technological University（南洋理工大学计算与数据科学学院）；Department of Data Science and Artificial Intelligence, The Hong Kong Polytechnic University（香港理工大学数据科学与人工智能系）
ComSD: Balancing Behavioral Quality and Diversity in Unsupervised Skill Discovery
Institute of Automation, Chinese Academy of Sciences（中国科学院自动化研究所）；University of Chinese Academy of Sciences（中国科学院大学）；Nanjing Institute of Software Technology（南京软件技术研究院）
