4 citations · 19 across the 14 of their papers we have counts for
15 papers
Communication-Efficient and Personalized Federated Lottery Ticket Learning
Sejin Seo, Seung-Woo Ko, Jihong Park +2
The lottery ticket hypothesis (LTH) claims that a deep neural network (i.e., ground network) contains a number of subnetworks (i.e., winning tickets), each of which exhibiting iden…
Exploiting User Mobility for WiFi RTT Positioning: A Geometric Approach
Kyuwon Han, Seung Min Yu, Seong-Lyun Kim +1
Recently, round-trip time (RTT) measured by a fine-timing measurement protocol has received great attention in the area of WiFi positioning. It provides an acceptable ranging accur…
Cooperative Multi-Point Vehicular Positioning Using Millimeter-Wave Surface Reflection (Extended version)
Zezhong Zhang, Seung-Woo Ko, Rui Wang +1
Multi-point vehicular positioning is one essential operation for autonomous vehicles. However, the state-of-the-art positioning technologies, relying on reflected signals from a ta…
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…
Random Access with Opportunity Detection in Wireless Networks
Jinho Choi, Seung-Woo Ko, Koji Yamamoto +1
This letter proposes a novel random medium access control (MAC) based on a transmission opportunity prediction, which can be measured in a form of a conditional success probability…
V2X-Based Vehicular Positioning: Opportunities, Challenges, and Future Directions
Seung-Woo Ko, Hyukjin Chae, Kaifeng Han +3
Vehicle-to-Everything (V2X) will create many new opportunities in the area of wireless communications, while its feasibility on enabling vehicular positioning has not been explored…