7 citations · 17 across the 15 of their papers we have counts for
8 papers · 1 filter
Energy-Efficient Vehicular Edge Computing with One-by-one Access Scheme
Youngsu Jang, Seongah Jeong, Joonhyuk Kang
With the advent of ever-growing vehicular applications, vehicular edge computing (VEC) has been a promising solution to augment the computing capacity of future smart vehicles. The…
Hybrid UAV-enabled Secure Offloading via Deep Reinforcement Learning
Seonghoon Yoo, Seongah Jeong, Joonhyuk Kang
Unmanned aerial vehicles (UAVs) have been actively studied as moving cloudlets to provide application offloading opportunities and to enhance the security level of user equipments…
End-to-End Fast Training of Communication Links Without a Channel Model via Online Meta-Learning
Sangwoo Park, Osvaldo Simeone, Joonhyuk Kang
When a channel model is not available, the end-to-end training of encoder and decoder on a fading noisy channel generally requires the repeated use of the channel and of a feedback…
Cooperative Learning via Federated Distillation over Fading Channels
Jin-Hyun Ahn, Osvaldo Simeone, Joonhyuk Kang
Cooperative training methods for distributed machine learning are typically based on the exchange of local gradients or local model parameters. The latter approach is known as Fede…
Meta-Learning to Communicate: Fast End-to-End Training for Fading Channels
Sangwoo Park, Osvaldo Simeone, Joonhyuk Kang
When a channel model is available, learning how to communicate on fading noisy channels can be formulated as the (unsupervised) training of an autoencoder consisting of the cascade…
Energy-Efficient Task Offloading for Vehicular Edge Computing: Joint Optimization of Offloading and Bit Allocation
Youngsu Jang, Jinyeop Na, Seongah Jeong +1
With the rapid development of vehicular networks, various applications that require high computation resources have emerged. To efficiently execute these applications, vehicular ed…