118 citations · 485 across the 87 of their papers we have counts for
15 papers · 1 filter
Multi-Site Clinical Federated Learning using Recursive and Attentive Models and NVFlare
Won Joon Yun, Samuel Kim, Joongheon Kim
The prodigious growth of digital health data has precipitated a mounting interest in harnessing machine learning methodologies, such as natural language processing (NLP), to scruti…
Cooperative Multi-Agent Deep Reinforcement Learning for Reliable and Energy-Efficient Mobile Access via Multi-UAV Control
Chanyoung Park, Soohyun Park, Soyi Jung +2
This paper addresses a novel multi-agent deep reinforcement learning (MADRL)-based positioning algorithm for multiple unmanned aerial vehicles (UAVs) collaboration (i.e., UAVs work…
Slimmable Quantum Federated Learning
Won Joon Yun, Jae Pyoung Kim, Soyi Jung +3
Quantum federated learning (QFL) has recently received increasing attention, where quantum neural networks (QNNs) are integrated into federated learning (FL). In contrast to the ex…
Search Space Adaptation for Differentiable Neural Architecture Search in Image Classification
Youngkee Kim, Soyi Jung, Minseok Choi +1
As deep neural networks achieve unprecedented performance in various tasks, neural architecture search (NAS), a research field for designing neural network architectures with autom…
SlimFL: Federated Learning with Superposition Coding over Slimmable Neural Networks
Won Joon Yun, Yunseok Kwak, Hankyul Baek +5
Federated learning (FL) is a key enabler for efficient communication and computing, leveraging devices' distributed computing capabilities. However, applying FL in practice is chal…
Feasibility Study of Multi-Site Split Learning for Privacy-Preserving Medical Systems under Data Imbalance Constraints in COVID-19, X-Ray, and Cholesterol Dataset
Yoo Jeong Ha, Gusang Lee, Minjae Yoo +3
It seems as though progressively more people are in the race to upload content, data, and information online; and hospitals haven't neglected this trend either. Hospitals are now a…