8 citations · 19 across the 15 of their papers we have counts for
15 papers
Neural Myerson Auction for Truthful and Energy-Efficient Autonomous Aerial Data Delivery
Haemin Lee, Sean Kwon, Soyi Jung +1
A successful deployment of drones provides an ideal solution for surveillance systems. Using drones for surveillance can provide access to areas that may be difficult or impossible…
Parallelized and Randomized Adversarial Imitation Learning for Safety-Critical Self-Driving Vehicles
Won Joon Yun, MyungJae Shin, Soyi Jung +2
Self-driving cars and autonomous driving research has been receiving considerable attention as major promising prospects in modern artificial intelligence applications. According t…
Communication and Energy Efficient Slimmable Federated Learning via Superposition Coding and Successive Decoding
Hankyul Baek, Won Joon Yun, Soyi Jung +4
Mobile devices are indispensable sources of big data. Federated learning (FL) has a great potential in exploiting these private data by exchanging locally trained models instead of…
Joint Superposition Coding and Training for Federated Learning over Multi-Width Neural Networks
Hankyul Baek, Won Joon Yun, Yunseok Kwak +5
This paper aims to integrate two synergetic technologies, federated learning (FL) and width-adjustable slimmable neural network (SNN) architectures. FL preserves data privacy by ex…
Spatio-Temporal Split Learning for Autonomous Aerial Surveillance using Urban Air Mobility (UAM) Networks
Yoo Jeong Ha, Soyi Jung, Jae-Hyun Kim +2
Autonomous surveillance unmanned aerial vehicles (UAVs) are deployed to observe the streets of the city for any suspicious activities. This paper utilizes surveillance UAVs for the…
Stable Marriage Matching for Traffic-Aware Space-Air-Ground Integrated Networks: A Gale-Shapley Algorithmic Approach
Hyunsoo Lee, Haemin Lee, Soyi Jung +1
In keeping with the rapid development of communication technology, a new communication structure is required in a next-generation communication system. In particular, research usin…
Trends in Neural Architecture Search: Towards the Acceleration of Search
Youngkee Kim, Won Joon Yun, Youn Kyu Lee +2
In modern deep learning research, finding optimal (or near optimal) neural network models is one of major research directions and it is widely studied in many applications. In this…
Introduction to Quantum Reinforcement Learning: Theory and PennyLane-based Implementation
Yunseok Kwak, Won Joon Yun, Soyi Jung +2
The emergence of quantum computing enables for researchers to apply quantum circuit on many existing studies. Utilizing quantum circuit and quantum differential programming, many r…
Spatio-Temporal Split Learning
Joongheon Kim, Seunghoon Park, Soyi Jung +1
This paper proposes a novel split learning framework with multiple end-systems in order to realize privacypreserving deep neural network computation. In conventional split learning…
Quantum Neural Networks: Concepts, Applications, and Challenges
Yunseok Kwak, Won Joon Yun, Soyi Jung +1
Quantum deep learning is a research field for the use of quantum computing techniques for training deep neural networks. The research topics and directions of deep learning and qua…
Quantum Scheduling for Millimeter-Wave Observation Satellite Constellation
Joongheon Kim, Yunseok Kwak, Soyi Jung +1
In beyond 5G and 6G network scenarios, the use of satellites has been actively discussed for extending target monitoring areas, even for extreme circumstances, where the monitoring…
Distributed and Autonomous Aerial Data Collection in Smart City Surveillance Applications
Haemin Lee, Soyi Jung, Joongheon Kim
The massive growth of Smart City and Internet of Things applications enables safety and security. The data those are produced from surveillance cameras in aerial devices such as un…
Secure Aerial Surveillance using Split Learning
Yoo Jeong Ha, Minjae Yoo, Soohyun Park +2
Personal monitoring devices such as cyclist helmet cameras to record accidents or dash cams to catch collisions have proliferated, with more companies producing smaller and compact…
Attention-based Reinforcement Learning for Real-Time UAV Semantic Communication
Won Joon Yun, Byungju Lim, Soyi Jung +4
In this article, we study the problem of air-to-ground ultra-reliable and low-latency communication (URLLC) for a moving ground user. This is done by controlling multiple unmanned…
Visualization of Deep Reinforcement Autonomous Aerial Mobility Learning Simulations
Gusang Lee, Won Joon Yun, Soyi Jung +2
This demo abstract presents the visualization of deep reinforcement learning (DRL)-based autonomous aerial mobility simulations. In order to implement the software, Unity-RL is use…