249 citations · 321 across the 38 of their papers we have counts for
12 papers · 1 filter
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…
Quality-Aware Deep Reinforcement Learning for Streaming in Infrastructure-Assisted Connected Vehicles
Won Joon Yun, Dohyun Kwon, Minseok Choi +3
This paper proposes a deep reinforcement learning-based video streaming scheme for mobility-aware vehicular networks, e.g., vehicles on the highway. We consider infrastructure-assi…
Delay-Sensitive and Power-Efficient Quality Control of Dynamic Video Streaming using Adaptive Super-Resolution
Minseok Choi, Won Joon Yun, Joongheon Kim
In a decade, the adaptive quality control of video streaming and the super-resolution (SR) technique have been deeply explored. As edge devices improved to have exceptional process…
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…
Joint Pilot Design and Channel Estimation using Deep Residual Learning for Multi-Cell Massive MIMO under Hardware Impairments
Byungju Lim, Won Joon Yun, Joongheon Kim +1
In multi-cell massive MIMO systems, channel estimation is deteriorated by pilot contamination and the effects of pilot contamination become more severe due to hardware impairments.…
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…
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…
Multi-Agent Deep Reinforcement Learning using Attentive Graph Neural Architectures for Real-Time Strategy Games
Won Joon Yun, Sungwon Yi, Joongheon Kim
In real-time strategy (RTS) game artificial intelligence research, various multi-agent deep reinforcement learning (MADRL) algorithms are widely and actively used nowadays. Most of…
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…