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연구

Research & Laboratory

제목
세미나 [10/29] Mobile Edge Intelligence at Scale
작성일
2018.10.19
작성자
전기전자공학부
게시글 내용

< BK21 플러스 BEST 정보기술 사업단 세미나 개최 안내 >


개최일시 : 2018 년 10월 29일 (월) 16:00 ~ 18:00

개최장소 : 제4공학관 D403호

세미나 제목 : Mobile Edge Intelligence at Scale

내용 :

In just a few years, breakthroughs in machine learning (ML) have transformed how computational models perform a wide variety of applications such as face recognition, autonomous driving, and language translation. Expanding its territory to mission-critical wireless applications makes the impossible become possible, e.g., supporting a massive number of devices with low latency and high reliability guarantees. This calls for a paradigm shift from classical ML to edge ML. To abide by the application’s low latency constraint, the inference in edge ML is operated at the network edges such as base stations (BSs) and mobile devices. Furthermore, the training process is performed locally at the edge side, and is collectively updated over the wirelessly connected edge devices, while not directly exchanging private data samples. Preserving data privacy enables the access to a huge amount of the user-generated training dataset, thereby improving the inference reliability. Unfortunately, traditional deep models and training algorithms exert severe demands on the energy/memory/communication resources of local devices, thus limiting their adoption for edge ML. Motivated by this, in this paper we explore the building blocks of edge ML, and propose its suitable theoretical and technical enablers, followed by several case studies demonstrating the effectiveness of our proposed approaches.

 

 

강연자 성함&직함 / 소속 : 박지홍 박사 / Oulu University, Finland

초청자 : 전기전자공학과 교수 김성륜