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제목
세미나 [06/22] Communication-Efficient Federated Machine Learning Frameworks
작성일
2019.06.13
작성자
전기전자공학부
게시글 내용

< BK21 플러스 BEST 정보기술 사업단 세미나 개최 안내 > 


개최일시 : 2019년 6월 22일 (토) 11:00 ~ 12:00

개최장소 : 제 4공학관 D403호

세미나 제목 : Communication-Efficient Federated Machine Learning Frameworks

내용 :

Recent advances in mobile computing power and machine learning (ML) have spurred on to the emergence of intelligent devices at the wireless network edge, ranging from phones and cameras to cars, drones, and robotic assemblers in smart factories. These devices generate private data by observing the surrounding environments, and run on-device ML models such as neural networks, thereby locally carrying out mission-critical decisions promptly. Since each single device observes a tiny fraction of the global environmental data, the on-device ML models should be trained collectively across devices over wireless links. This calls for a novel distributed ML framework that is suited for wireless connectivity while preserving local data privacy, termed federated machine learning (FML). In this talk, promising communication-efficient FML frameworks will be outlined, wherein on-device ML models are trained by their exchanging: model parameters, model outputs, and/or local data with privacy guarantees. Their effectiveness will be discussed in supervised, unsupervised, and reinforcement learning applications, under different channel dynamics and network architectures, as well as data distributions and privacy guarantee requirements.



강연자 성함&직함 / 소속 : Jihong Park, Post Doctoral Researcher / University of Oulu, Finland 

초청자 : 전기전자공학과 교수 김성륜