• Communication Efficient Federated Learning

    發布時間:2020-11-16瀏覽次數:52

    講座題目: Communication Efficient Federated Learning

    講座嘉賓😭:金耀初🕵🏽‍♀️,薩裏大學教授

    講座時間🎺: 2020年11月16號周一🏌🏽,下午16:00-17:00

    講座地點🧏🏻:騰訊會議,https://meeting.tencent.com/s/oyzKAAY3PKSs,會議ID:976 179 984

     

    內容摘要Federated learning is a new distributed learning paradigm that can preserve data privacy in machine learning. One of the main challenges in federated learning is to reduce the communication costs for transmitting model parameters between local devices and the central server and vice versa. This talk presents some most recent work on communication efficient federated learning, including constructing compact local models, introducing layer-wise asynchronous parameter update, and using ternary quantization. At the end of the talk, future directions of research in federated learning will be briefly discussed.

     

    講座嘉賓簡介:

          Yaochu Jin received the BSc, MSc, and PhD degrees from Zhejiang University, Hangzhou, China, in 1988, 1991, and 1996, respectively, and the Dr.-Ing. degree from Ruhr University Bochum, Germany, in 2001.

         Dr Jin is currently a Distinguished Chair Professor in Computational Intelligence, Department of Computer Science, University of Surrey, Guildford, U.K., where he heads the Nature Inspired Computing and Engineering Group. He was a “Finland Distinguished Professor” of University of Jyvaskyla, Finland, and “Changjiang Distinguished Visiting Professor”, Northeastern University, China. His main research interests include data-driven surrogate-assisted evolutionary optimization, trustworthy machine learning, multi-objective evolutionary learning, swarm robotics, and evolutionary developmental systems.

        Dr Jin is presently the Editor-in-Chief of the IEEE TRANSACTIONS ON COGNITIVE AND DEVELOPMENTAL SYSTEMS and the Editor-in-Chief of Complex & Intelligent Systems. He is the recipient of the 2018 and 2020 IEEE Transactions on Evolutionary Computation Outstanding Paper Award, and the 2014, 2016, and 2019 IEEE Computational Intelligence Magazine Outstanding Paper Award. He is named as a Highly Cited Researcher 2019 by the Web of Science Group. He is a Fellow of IEEE.

     

     

         歡迎廣大師生進行線上交流!

     

     

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