3 papers
cs.LG2024
Energy-Efficient Edge Learning via Joint Data Deepening-and-Prefetching
Sujin Kook, Won-Yong Shin, Seong-Lyun Kim +1
The vision of pervasive artificial intelligence (AI) services can be realized by training an AI model on time using real-time data collected by internet of things (IoT) devices. To…
cs.NI2022
Joint Data Deepening-and-Prefetching for Energy-Efficient Edge Learning
Sujin Kook, Won-Yong Shin, Seong-Lyun Kim +1
The vision of pervasive machine learning (ML) services can be realized by training an ML model on time using real-time data collected by internet of things (IoT) devices. To this e…
cs.IT2020
Understanding Uncertainty of Edge Computing: New Principle and Design Approach
Sejin Seo, Sang Won Choi, Sujin Kook +2
Due to the edge's position between the cloud and the users, and the recent surge of deep neural network (DNN) applications, edge computing brings about uncertainties that must be u…