概述
日期
2024年01月26日
09:00 - 10:00
地点
活动行、Bilibili

Personalized Federated Learning and Its Application in 360-degree Video Streaming

联邦学习是一种允许多个边缘设备协作训练一个模型的分布式人工智能框架，而个性化联邦学习可以解决数据异构性和设备异构性问题。在360度视频流媒体的领域中，个性化联邦学习算法可以用于训练用户的头部移动预测模型，该预测模型是基于内容的视口预测框架中的重要组成部分。

第十二期AIRS-TNSE联合杰出讲座系列活动，我们有幸邀请到Vincent Wong教授介绍个性化联邦学习及其在360度视频流媒体中的应用，并分享他在这个领域内的相关研究成果与有趣发现。

AIRS-TNSE Joint Distinguished Seminar Series is co-sponsored by IEEE Transactions on Network Science and Engineering (TNSE) and Shenzhen Institute of Artificial Intelligence and Robotics for Society (AIRS), with joint support from The Chinese University of Hong Kong, Shenzhen, Network Communication and Economics Laboratory (NCEL), and IEEE. This series aims to bring together top international experts and scholars in the field of network science and engineering to share cutting-edge scientific and technological achievements.

Join the seminar through Bilibili (http://live.bilibili.com/22587709).

  • Jianwei Huang
    Vice President, AIRS; Presidential Chair Professor, CUHK-Shenzhen; Editor-in-Chief, IEEE TNSE; IEEE Fellow; AAIA Fellow
    Executive Chair
  • Vincent Wong
    Professor in the Department of Electrical and Computer Engineering, Universityof British Columbia; Editor-in-Chief of the lEEE Transactlons on Wireless Communications; IEEE Fellow
    Personalized Federated Learning and Its Application in 360-degree Video Streaming

    Vincent Wong教授是英属哥伦比亚大学电气与计算机工程系的教授。他的研究领域包括通信网络的协议设计、优化和资源管理，涉及到互联网、无线网络、智能电网、移动边缘计算和物联网等应用。目前，Vincent Wong教授担任IEEE Transactions on Wireless Communications的主编。2016年，他获评IEEE fellow。

    Federated learning is a distributed artificial intelligence framework, which allows multiple edge devices to train a single model collaboratively. In this talk, we first introduce a personalized federated learning algorithm which can tackle the issues of data heterogeneity and device heterogeneity. Then, we present a content-based viewport prediction framework for 360-degree video streaming, wherein users’ head movement prediction models are trained using a personalized federated learning algorithm. The output of the viewport prediction framework corresponds to which video tiles to be transmitted. Finally, we present an algorithm to determine the bitrate and beamforming matrices in a THz-enabled 360-degree video streaming system with multiple access points.

Video Archive

活动回顾 | Vincent Wong教授：个性化联邦学习及其应用