activity
20152022
most citedExtreme URLLC: Vision, Challenges, and Key Enablers

104 citations · 337 across the 33 of their papers we have counts for

collaborators

56 papers

quant-ph20224 cited

Quantum Federated Learning with Entanglement Controlled Circuits and Superposition Coding

Won Joon Yun, Jae Pyoung Kim, Hankyul Baek +4

While witnessing the noisy intermediate-scale quantum (NISQ) era and beyond, quantum federated learning (QFL) has recently become an emerging field of study. In QFL, each quantum c…

cs.DC20224 cited

Differentially Private CutMix for Split Learning with Vision Transformer

Seungeun Oh, Jihong Park, Sihun Baek +5

Recently, vision transformer (ViT) has started to outpace the conventional CNN in computer vision tasks. Considering privacy-preserving distributed learning with ViT, federated lea…

cs.IT2022

Predictive Closed-Loop Remote Control over Wireless Two-Way Split Koopman Autoencoder

Abanoub M. Girgis, Hyowoon Seo, Jihong Park +2

Real-time remote control over wireless is an important-yet-challenging application in 5G and beyond due to its mission-critical nature under limited communication resources. Curren…

quant-ph20222 cited

Quantum Multi-Agent Reinforcement Learning via Variational Quantum Circuit Design

Won Joon Yun, Yunseok Kwak, Jae Pyoung Kim +4

In recent years, quantum computing (QC) has been getting a lot of attention from industry and academia. Especially, among various QC research topics, variational quantum circuit (V…

cs.MA2021

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…

cs.LG2021

Robust Reconfigurable Intelligent Surfaces via Invariant Risk and Causal Representations

Sumudu Samarakoon, Jihong Park, Mehdi Bennis

In this paper, the problem of robust reconfigurable intelligent surface (RIS) system design under changes in data distributions is investigated. Using the notion of invariant risk…