249 citations · 440 across the 6 of their papers we have counts for
6 papers
Cooperative Multi-Agent Deep Reinforcement Learning for Reliable Surveillance via Autonomous Multi-UAV Control
Won Joon Yun, Soohyun Park, Joongheon Kim +4
CCTV-based surveillance using unmanned aerial vehicles (UAVs) is considered a key technology for security in smart city environments. This paper creates a case where the UAVs with…
Adversarial Imitation Learning via Random Search in Lane Change Decision-Making
Myungjae Shin, Joongheon Kim
As the advanced driver assistance system (ADAS) functions become more sophisticated, the strategies that properly coordinate interaction and communication among the ADAS functions…
Adversarial Imitation Learning via Random Search
MyungJae Shin, Joongheon Kim
Developing agents that can perform challenging complex tasks is the goal of reinforcement learning. The model-free reinforcement learning has been considered as a feasible solution…
XOR Mixup: Privacy-Preserving Data Augmentation for One-Shot Federated Learning
MyungJae Shin, Chihoon Hwang, Joongheon Kim +3
User-generated data distributions are often imbalanced across devices and labels, hampering the performance of federated learning (FL). To remedy to this non-independent and identi…
Auction-based Charging Scheduling with Deep Learning Framework for Multi-Drone Networks
MyungJae Shin, Joongheon Kim, Marco Levorato
State-of-the-art drone technologies have severe flight time limitations due to weight constraints, which inevitably lead to a relatively small amount of available energy. Therefore…
Randomized Adversarial Imitation Learning for Autonomous Driving
MyungJae Shin, Joongheon Kim
With the evolution of various advanced driver assistance system (ADAS) platforms, the design of autonomous driving system is becoming more complex and safety-critical. The autonomo…