Qiang Yang Federated Learning

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Federated Learning - Qiang Yang, Yang Liu, Yong Cheng, …

(6 days ago) This book shows how federated machine learning allows multiple data owners to collaboratively train and use a shared prediction model while keeping all the local training data private. Traditional machine learning approaches need to combine all data at one location, typically a data center, which may very well violate the laws on user privacy and data …

https://books.google.com/books/about/Federated_Learning.html?id=JdPGDwAAQBAJ

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Federated Learning – FedAI.org

(5 days ago) Qiang Yang. Yang Liu. Yong Cheng. Yan Kang. Tianjian Chen. Han Yu. In this book, we describe how federated machine learning addresses this problem with novel solutions combining distributed machine learning, cryptography and security, and incentive mechanism design based on economic principles and game theory. We explain different types of

https://www.fedai.org/research/book/federated-learning/

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Federated Learning by Qiang Yang

(3 days ago) Federated Learning book. Read reviews from world’s largest community for readers. How is it possible to allow multiple data owners to collaboratively tra

https://www.goodreads.com/book/show/50683911-federated-learning

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Federated Learning (Synthesis Lectures on Artificial

(9 days ago) Federated Learning (Synthesis Lectures on Artificial Intelligence and Machine Le) [Yang, Qiang, Liu, Yang, Cheng, Yong] on Amazon.com. *FREE* shipping on qualifying offers. Federated Learning (Synthesis Lectures on Artificial Intelligence and Machine Le)

https://www.amazon.com/Federated-Learning-Synthesis-Artificial-Intelligence/dp/1681736977

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QIANG YANG, YANG LIU, TIANJIAN CHEN, …

(3 days ago) 12 Federated Machine Learning: Concept and Applications QIANG YANG,Hong Kong University of Science and Technology, Hong Kong YANG LIU,Webank, China TIANJIAN CHEN,Webank, China YONGXIN TONG,Beihang

https://www.researchgate.net/profile/Tianjian-Chen-3/publication/331086697_Federated_Machine_Learning_Concept_and_Applications/links/602fc91c92851c4ed580d7f8/Federated-Machine-Learning-Concept-and-Applications.pdf

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[2103.00710] Towards Personalized Federated Learning

(2 days ago) Towards Personalized Federated Learning. Authors: Alysa Ziying Tan, Han Yu, Lizhen Cui, Qiang Yang. Download PDF. Abstract: As artificial intelligence (AI)-empowered applications become widespread, there is growing awareness and concern for user privacy and data confidentiality. This has contributed to the popularity of federated learning (FL).

https://arxiv.org/abs/2103.00710

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(PDF) Federated Machine Learning: Concept and …

(2 days ago) We provide definitions, architectures and applications for the federated learning framework, and provide a comprehensive survey of existing works …

https://www.researchgate.net/publication/331086697_Federated_Machine_Learning_Concept_and_Applications

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Threats to Federated Learning: A Survey - GroundAI

(3 days ago) Qiang Yang, Yang Liu, Tianjian Chen, and Yongxin Tong. Federated machine learning: Concept and applications. ACM Transactions on Intelligent Systems and Technology (TIST), 10(2):1–19, 2019. Qiang Yang, Yang Liu, Yong Cheng, Yan Kang, Tianjian Chen, and Han Yu. Federated Learning. Morgan & Claypool Publishers, 2019.

https://www.groundai.com/project/threats-to-federated-learning-a-survey/1

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[1901.08277] Federated Deep Reinforcement Learning

(2 days ago) In deep reinforcement learning, building policies of high-quality is challenging when the feature space of states is small and the training data is limited. Despite the success of previous transfer learning approaches in deep reinforcement learning, directly transferring data or models from an agent to another agent is often not allowed due to the privacy of data and/or …

https://arxiv.org/abs/1901.08277

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FTL-IJCAI'21 - Federated Learning

(5 days ago) Title: A Journey from Transfer Learning to Federated Learning Speaker: Qiang Yang, Chief AI Officer (CAIO), WeBank / Chair Professor, Hong Kong University of Science and Technology (HKUST) Biography Qiang Yang is the head of the AI Department at WeBank (Chief AI Officer) and Chair Professor at the Computer Science and Engineering (CSE) Department of the Hong …

https://federated-learning.org/fl-ijcai-2021/

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COMP 6211G: Federated Learning (Spring 2021) - iSING Lab

(8 days ago) Federated Learning Qiang Yang, Yang Liu, Yong Cheng, Yan Kang, Tianjian Chen, Han Yu Morgan & Claypool Publishers, 2019

https://ising.cse.ust.hk/fl/index.html

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Federated Learning by Qiang Yang, Yang Liu, Yong Cheng

(3 days ago) Yang Liu is a Senior Researcher in the AI Department of WeBank, China. Her research interests include machine learning, federated learning, transfer learning, multi-agent systems, statistical mechanics, and applications of these technologies in the financial industry.

https://www.barnesandnoble.com/w/federated-learning-qiang-yang/1135692959

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Federated Learning by Qiang Yang, Yang Liu, Yong Cheng

(7 days ago) This book shows how federated machine learning allows multiple data owners to collaboratively train and use a shared prediction model while keeping all the local training data private. Traditional machine learning approaches need to combine all data at one location, typically a data center

https://preview.barnesandnoble.com/w/federated-learning-qiang-yang/1135692959

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Federated Learning by Qiang Yang · OverDrive: ebooks

(8 days ago) This book shows how federated machine learning allows multiple data owners to collaboratively train and use a shared prediction model while keeping all the local training data private. Traditional machine learning approaches need to combine all data at one location, typically a data center, which may very well violate the laws on user privacy

https://www.overdrive.com/media/6941829/federated-learning

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Federated Learning - Qiang Yang, Yang Liu, Yong Cheng

(6 days ago) Federated Learning Qiang Yang , Yang Liu , Yong Cheng , Tianjian Chen , Han Yu Morgan & Claypool Publishers , Dec 19, 2019 - Federated database systems -

https://books.google.com/books/about/Federated_Learning.html?id=Jj6TzAEACAAJ

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FedAI.org – Federated AI Ecosystem

(2 days ago) Hankz Hankui Zhuo, Wenfeng Feng, Qian Xu, Qiang Yang, Yufeng Lin. SecureBoost: A Lossless Federated Learning Framework Kewei Cheng, Tao Fan, Yilun Jin, Yang Liu, Tianjian Chen, Qiang Yang. Federated Machine Learning: Concept and Applications Qiang Yang, Yang Liu, Tianjian Chen, Yongxin Tong.

https://www.fedai.org/

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AAAI-20 / IAAI-20 / EAAI-20 Program

(5 days ago) form Powered by Federated Learning Yang Liu, Anbu Huang, Yun Luo, He Huang, Youzhi Liu, Yuanyuan Chen, Lican Feng, Tianjian Chen, Han Yu, Qiang Yang Feedback-Based Self-Learning in Large-Scale Conver-sational AI Agents Pragaash Ponnusamy, Alireza Roshan Ghias, Chenlei Guo, Ruhi Sarikaya How Machine Learning Is Improving U.S. Navy Cus-tomer …

https://aaai.org/Conferences/AAAI-20/wp-content/uploads/2020/02/AAAI20-ProgramWeb.pdf

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Federated Learning Synthesis Lectures on Artificial

(8 days ago) Yang Liu, Han Yu, Qiang Yang ‌. (2020) Introduction to the Special Issue on Federated Machine Learning. (2020) Introduction to the Special Issue on Federated Machine Learning. IEEE Intelligent Systems 35 :4, 3-4.

https://www.morganclaypool.com/doi/10.2200/S00960ED2V01Y201910AIM043

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FATE: An Industrial Grade Platform for Collaborative

(Just Now) In contrast to traditional distributed learning, federated learning (McMahan et al., 2016; Yang et al., 2019) is proposed to tackle data locality and privacy in various cross-device and cross-silo scenarios, (Kairouz et al., 2019; Li et al., 2019) by allowing model updates

https://jmlr.csail.mit.edu/papers/volume22/20-815/20-815.pdf

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Multi-Agent Visualization for Explaining Federated Learning

(7 days ago) Multi-Agent Visualization for Explaining Federated Learning Xiguang Wei1, Quan Li1, Yang Liu1;2, Han Yu4, Tianjian Chen1 and Qiang Yang1;3 1AI Group, WeBank 2The Joint NTU-WeBank Research Centre of Eco-Intelligent Applications (THEIA) 3Department of Computer Science and Engineering, Hong Kong University of Science and Technology 4School of …

https://www.ijcai.org/Proceedings/2019/0960.pdf

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Series Editors: Federated

(6 days ago) QIANG YANG • ET AL FEDERATED LEARNING MORGAN & CLAYPOOL Series ISSN: 1939-4608 Ronald J. Brachman, Francesca Rossi, and Peter Stone, Series Editors Federated Learning Qiang Yang Yang Liu Yong Cheng Yan Kang Tianjian Chen Han Yu. FederatedLearning. SynthesisLecturesonArtificial IntelligenceandMachine

https://www.morganclaypoolpublishers.com/catalog_Orig/samples/9781681736983_sample.pdf

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Hierarchical Incentive Mechanism Design for Federated

(5 days ago) To this end, we propose a federated learning (FL)-based privacy-preserving approach to facilitate collaborative machine learning among multiple model owners in mobile crowdsensing. The work of Qiang Yang was supported by the Hong Kong CERG under Grant 16209715 and Grant 16244616. (Corresponding author: Zehui Xiong.) Wei Yang Bryan Lim is

https://collaborate.princeton.edu/en/publications/hierarchical-incentive-mechanism-design-for-federated-machine-lea

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FedVision: An Online Visual Object Detection Platform

(3 days ago) Federated learning (FL) is a promising approach to resolve this challenge. Nevertheless, there currently lacks an easy to use tool to enable computer vision application developers who are not experts in federated learning to conveniently leverage this technology and apply it in their systems. Qiang Yang The Hong Kong University of Science

https://ojs.aaai.org/index.php/AAAI/article/view/7021

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Federated Learning - HKUST SPD The Institutional Repository

(9 days ago) Federated Learning. Federated Learning / by Qiang Yang, Yang Liu, Yong Cheng, Yan Kang, Tianjian Chen, and Han Yu. Morgan & Claypool , 2020. Book series: Synthesis Lectures on Artificial Intelligence and Machine Learning, v. 13, (3). How is it possible to allow multiple data owners to collaboratively train and use a shared prediction model

https://repository.ust.hk/ir/Record/1783.1-104222

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‪Qiang Yang (杨强)‬ - ‪Google Scholar‬

(7 days ago) Qiang Yang (杨强). Chief AI [email protected], Chair [email protected] HKUST, IJCAI President 2017-19, AAAI-21 General Chair. Verified email at cse.ust.hk - Homepage. Artificial Intelligence Transfer Learning Federated Learning Machine Learning and Data Mining. Articles Cited by Public access Co-authors.

https://scholar.google.com.sg/citations?user=1LxWZLQAAAAJ&hl=en

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FL-IJCAI'19 - Federated Learning

(5 days ago) Attention-Based Updates Aggregation in Federated Learning; Kewei Cheng, Tao Fan, Yilun Jin, Yang Liu, Tianjian Chen and Qiang Yang. SecureBoost: A Lossless Federated Learning Framework; Kun Zhao, Haoyuan Zheng, Wei Xi, Zhi Wang, Wei Shi, Liang Lin and Jizhong Zhao. SFL: Secure Federated Learning based on Jaccard Coefficient Threshold

https://federated-learning.org/fl-ijcai-2019/

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A Multi-player Game for Studying Federated Learning

(7 days ago) A Multi-player Game for Studying Federated Learning Incentive Schemes Kang Loon Ng1, Zichen Chen2, Zelei Liu1, Han Yu1;2, Yang Liu3y and Qiang Yang3;4 1School of Computer Science and Engineering, Nanyang Technological University (NTU), Singapore 2Joint NTU-WeBank Research Centre on FinTech, NTU, Singapore 3Department of AI, WeBank, …

https://www.ijcai.org/Proceedings/2020/0769.pdf

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‎Federated Learning in Apple Books

(3 days ago) This book provides a comprehensive and self-contained introduction to Federated Learning, ranging from the basic knowledge and theories to various key applications, and the privacy and incentive factors are the focus of the whole book. This book is timely needed since Federated Learning is getting p…

https://books.apple.com/nl/book/federated-learning/id1542156303

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Top Resources To Learn About Federated Learning

(8 days ago) Authored by Qiang Yang, Yang Liu, Yong Cheng, Yan Kang, Tianjin Chen and Han Yu, this book on federated learning provides consolidated information on federated learning. Spread across eleven chapters, this book trains readers to collaboratively train and use shared prediction models while keeping local training data private.

https://analyticsindiamag.com/top-resources-to-learn-about-federated-learning/

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‎Federated Learning on Apple Books

(3 days ago) ‎This book provides a comprehensive and self-contained introduction to Federated Learning, ranging from the basic knowledge and theories to various key applications, and the privacy and incentive factors are the focus of the whole book. This book is timely needed since Federated Learning is getting p…

https://books.apple.com/us/book/federated-learning/id1542156303

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Authors’ Biographies – Federated Learning – w3sdev

(2 days ago) Authors’ Biographies. QIANG YANG. Qiang Yang is the head of the AI department at WeBank (Chief AI Officer) and Chair Professor at the Computer Science and Engineering (CSE) Department of the Hong Kong University of Science and Technology (HKUST), where he was a former head of CSE Department and founding director of the Big Data Institute (2015–2018).

https://w3sdev.com/authors-biographies-federated-learning.html

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Federated Machine Learning: Concept and Applications: ACM

(8 days ago) Qiang Yang, Yang Liu, Tianjian Chen, and Yongxin Tong. 2018. Federated learning. Communications of the CCF 14, 11 (2018), 49--55. Google Scholar; Andrew C. Yao. 1982. Protocols for secure computations. In Proceedings of the 23rd Annual Symposium on Foundations of Computer Science (SFCS’82).

https://dl.acm.org/doi/10.1145/3298981

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GitHub - lee-man/federated-learning: Related material on

(5 days ago) Federated Machine Learning: Concept and Applications from Qiang Yang, etc. link; Federated Learning for Mobile Keyboard Prediction by Google. link. Federated Optimization: Distributed Machine Learning for On-Device Intelligence from Google. link. Towards Federated Learning at Scale: System Design from Google. link

https://github.com/lee-man/federated-learning

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Project Highlights - trustful.federated-learning.org

(3 days ago) Yang Liu, Anbu Huang, Yun Luo, He Huang, Youzhi Liu, Yuanyuan Chen, Lican Feng, Tianjian Chen, Han Yu & Qiang Yang, "FedVision: An Online Visual Object Detection Platform Powered by Federated Learning," in Proceedings of the 32nd Annual Conference on Innovative Applications of Artificial Intelligence (IAAI-20), pp. 13172-13179, 2020.

https://trustful.federated-learning.org/projects.html

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Dashan Gao’s Page This is Dashan Gao’s homepage. I am

(8 days ago) This is Dashan Gao’s homepage. I am currently a PhD student in Hong Kong University of Science and Technology. My research interest includs federated learning, privacy-preserving machine learning, and transfer learning. This homepage shares some research progress.

https://dashangao.github.io/

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Advances and open problems in federated learning

(5 days ago) Federated learning (FL) is a machine learning setting where many clients (e.g., mobile devices or whole organizations) collaboratively train a model under the orchestration of a central server (e.g., service provider), while keeping the training data decentralized. FL embodies the principles of focused data collection and minimization, and can

https://experts.illinois.edu/en/publications/advances-and-open-problems-in-federated-learning-2

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[PDF] Federated Machine Learning Semantic Scholar

(4 days ago) DOI: 10.1145/3298981 Corpus ID: 59337327. Federated Machine Learning @article{Yang2019FederatedML, title={Federated Machine Learning}, author={Qiang Yang and Yang Liu and Tianjian Chen and Yongxin Tong}, journal={ACM Transactions on Intelligent Systems and Technology (TIST)}, year={2019}, volume={10}, pages={1 - 19} }

https://www.semanticscholar.org/paper/Federated-Machine-Learning-Yang-Liu/62ccd99a65bfc7c735ae1f33b75b107665de95df

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Publications ‹ Ramesh Raskar — MIT Media Lab

(8 days ago) FedML: A Research Library and Benchmark for Federated Machine Learning Chaoyang He, Songze Li, Jinhyun So, Mi Zhang, Xiao Zeng, Hongyi Wang, Xiaoyang Wang, Praneeth Vepakomma, Abhishek Singh, Hang Qiu, Xinghua Zhu, Jianzong Wang, Li Shen, Peilin Zhao, Yan Kang, Yang Liu, Ramesh Raskar, Qiang Yang, Murali Annavaram and Salman Avestimehr.

https://www-prod.media.mit.edu/people/raskar/publications/

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Federated Learning - Morgan Claypool Publishers

(7 days ago) Yang Liu, WeBank, China Yang Liu is a Senior Researcher in the AI Department of WeBank, China. Her research interests include machine learning, federated learning, transfer learning, multi-agent systems, statistical mechanics, and applications of these technologies in …

https://www.morganclaypoolpublishers.com/catalog_Orig/product_info.php?products_id=1494

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Hierarchical incentive mechanism design for federated

(Just Now) Hierarchical Incentive Mechanism Design for Federated Machine Learning in Mobile Networks Wei Yang Bryan Lim, Zehui Xiong, Chunyan Miao, Senior Member, IEEE, Dusit Niyato, Fellow, IEEE, Qiang Yang, Fellow, IEEE, Cyril Leung, Life Member, IEEE, H. Vincent Poor, Fellow, IEEE Abstract—In recent years, the enhanced sensing and com-

https://dr.ntu.edu.sg/bitstream/10356/144299/2/Hierarchical%20Incentive%20Mechanism%20Design%20for%20Federated%20Machine%20Learning%20in%20Mobile%20Networks.pdf

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Standardization of Federated Machine Learning

(9 days ago) In this event, you will hear from two of the top minds in Federated Machine Learning (FML) as they discuss identified challenges and potential impacts, and speak to the newly published standard IEEE 3652.1-2020 about FML. Prof. Qiang Yang, Fellow of Royal Society of Canada (RSC) and Canadian Academy of Engineering (CAE), Chief Artificial

https://engagestandards.ieee.org/FT-Federated-Learning.html

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Federated Learning eBook by Qiang Yang - 9781681737188

(1 days ago) Read "Federated Learning" by Qiang Yang available from Rakuten Kobo. This book shows how federated machine learning allows multiple data owners to collaboratively train and use a shared pre

https://www.kobo.com/hk/en/ebook/federated-learning

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Publications - trustful.federated-learning.org

(7 days ago) Zelei Liu, Yuanyuan Chen, Yansong Zhao, Han Yu, Yang Liu, Renyi Bao, Jinpeng Jiang, Zaiqing Nie, Qian Xu & Qiang Yang, "Contribution-Aware Federated Learning for Smart Healthcare," in Proceedings of the 34th Annual Conference on Innovative Applications of Artificial Intelligence (IAAI-22), 2022.(Innovative Applications of AI Award)Xiaojie Guo, Shugen Wang, Hanqing …

https://trustful.federated-learning.org/publications.html

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