Search Results for author: Won Joon Yun

Found 28 papers, 1 papers with code

Multi-Site Clinical Federated Learning using Recursive and Attentive Models and NVFlare

no code implementations28 Jun 2023 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 scrutinize medical records, clinical notes, and other text-based health information.

Decision Making Federated Learning

Quantum Multi-Agent Actor-Critic Networks for Cooperative Mobile Access in Multi-UAV Systems

no code implementations9 Feb 2023 Chanyoung Park, Won Joon Yun, Jae Pyoung Kim, Tiago Koketsu Rodrigues, Soohyun Park, Soyi Jung, Joongheon Kim

This paper proposes a novel algorithm, named quantum multi-agent actor-critic networks (QMACN) for autonomously constructing a robust mobile access system employing multiple unmanned aerial vehicles (UAVs).

Multi-agent Reinforcement Learning

Situation-Aware Deep Reinforcement Learning for Autonomous Nonlinear Mobility Control in Cyber-Physical Loitering Munition Systems

no code implementations31 Dec 2022 Hyunsoo Lee, Soohyun Park, Won Joon Yun, Soyi Jung, Joongheon Kim

Thus, our proposed autonomous nonlinear drone mobility control algorithm utilizes situation-aware components those are implemented with a Raycast function in Unity virtual scenarios.

Unity

Coordinated Multi-Agent Reinforcement Learning for Unmanned Aerial Vehicle Swarms in Autonomous Mobile Access Applications

no code implementations23 Dec 2022 Chanyoung Park, Haemin Lee, Won Joon Yun, Soyi Jung, Joongheon Kim

This paper proposes a novel centralized training and distributed execution (CTDE)-based multi-agent deep reinforcement learning (MADRL) method for multiple unmanned aerial vehicles (UAVs) control in autonomous mobile access applications.

Multi-agent Reinforcement Learning reinforcement-learning

Quantum Federated Learning with Entanglement Controlled Circuits and Superposition Coding

no code implementations4 Dec 2022 Won Joon Yun, Jae Pyoung Kim, Hankyul Baek, Soyi Jung, Jihong Park, Mehdi Bennis, Joongheon Kim

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

Federated Learning Image Classification

Software Simulation and Visualization of Quantum Multi-Drone Reinforcement Learning

no code implementations24 Nov 2022 Chanyoung Park, Jae Pyoung Kim, Won Joon Yun, Soohyun Park, Soyi Jung, Joongheon Kim

Quantum machine learning (QML) has received a lot of attention according to its light training parameter numbers and speeds; and the advances of QML lead to active research on quantum multi-agent reinforcement learning (QMARL).

Multi-agent Reinforcement Learning Quantum Machine Learning +2

Quantum Split Neural Network Learning using Cross-Channel Pooling

no code implementations12 Nov 2022 Won Joon Yun, Hankyul Baek, Joongheon Kim

In recent years, the field of quantum science has attracted significant interest across various disciplines, including quantum machine learning, quantum communication, and quantum computing.

Federated Learning Privacy Preserving +2

Projection Valued Measure-based Quantum Machine Learning for Multi-Class Classification

no code implementations30 Oct 2022 Won Joon Yun, Hankyul Baek, Joongheon Kim

In recent years, quantum machine learning (QML) has been actively used for various tasks, e. g., classification, reinforcement learning, and adversarial learning.

Multi-class Classification Quantum Machine Learning

3D Scalable Quantum Convolutional Neural Networks for Point Cloud Data Processing in Classification Applications

no code implementations18 Oct 2022 Hankyul Baek, Won Joon Yun, Joongheon Kim

Moreover, a quantum convolutional neural network (QCNN) is the quantum-version of CNN because it can process high-dimensional vector inputs in contrast to QNN.

Self-Configurable Stabilized Real-Time Detection Learning for Autonomous Driving Applications

no code implementations29 Sep 2022 Won Joon Yun, Soohyun Park, Joongheon Kim, David Mohaisen

In addition, we demonstrate the self-configurable stabilized detection with YOLOv3-tiny and FlowNet2-S, which are the real-time object detection network and an optical flow estimation network, respectively.

Autonomous Driving Object +3

Scalable Quantum Convolutional Neural Networks

no code implementations26 Sep 2022 Hankyul Baek, Won Joon Yun, Joongheon Kim

With the beginning of the noisy intermediate-scale quantum (NISQ) era, quantum neural network (QNN) has recently emerged as a solution for the problems that classical neural networks cannot solve.

Spatio-Temporal Attack Course-of-Action (COA) Search Learning for Scalable and Time-Varying Networks

no code implementations2 Sep 2022 Haemin Lee, Seok Bin Son, Won Joon Yun, Joongheon Kim, Soyi Jung, Dong Hwa Kim

One of the key topics in network security research is the autonomous COA (Couse-of-Action) attack search method.

Quantum Multi-Agent Meta Reinforcement Learning

no code implementations22 Aug 2022 Won Joon Yun, Jihong Park, Joongheon Kim

Although quantum supremacy is yet to come, there has recently been an increasing interest in identifying the potential of quantum machine learning (QML) in the looming era of practical quantum computing.

Meta-Learning Meta Reinforcement Learning +4

Slimmable Quantum Federated Learning

no code implementations20 Jul 2022 Won Joon Yun, Jae Pyoung Kim, Soyi Jung, Jihong Park, Mehdi Bennis, Joongheon Kim

Quantum federated learning (QFL) has recently received increasing attention, where quantum neural networks (QNNs) are integrated into federated learning (FL).

Federated Learning

SlimFL: Federated Learning with Superposition Coding over Slimmable Neural Networks

no code implementations26 Mar 2022 Won Joon Yun, Yunseok Kwak, Hankyul Baek, Soyi Jung, Mingyue Ji, Mehdi Bennis, Jihong Park, Joongheon Kim

However, applying FL in practice is challenging due to the local devices' heterogeneous energy, wireless channel conditions, and non-independently and identically distributed (non-IID) data distributions.

Distributed Computing Federated Learning

Quantum Distributed Deep Learning Architectures: Models, Discussions, and Applications

no code implementations19 Feb 2022 Yunseok Kwak, Won Joon Yun, Jae Pyoung Kim, Hyunhee Cho, Minseok Choi, Soyi Jung, Joongheon Kim

Although deep learning (DL) has already become a state-of-the-art technology for various data processing tasks, data security and computational overload problems often arise due to their high data and computational power dependency.

Two-stage architectural fine-tuning with neural architecture search using early-stopping in image classification

no code implementations17 Feb 2022 Youngkee Kim, Won Joon Yun, Youn Kyu Lee, Soyi Jung, Joongheon Kim

In many deep neural network (DNN) applications, the difficulty of gathering high-quality data in the industry field hinders the practical use of DNN.

Image Classification Neural Architecture Search +1

Parallelized and Randomized Adversarial Imitation Learning for Safety-Critical Self-Driving Vehicles

no code implementations26 Dec 2021 Won Joon Yun, MyungJae Shin, Soyi Jung, Sean Kwon, Joongheon Kim

The RAIL is a novel derivative-free imitation learning method for autonomous driving with various ADAS functions coordination; and thus it imitates the operation of decision maker that controls autonomous driving with various ADAS functions.

Autonomous Driving Imitation Learning +1

Communication and Energy Efficient Slimmable Federated Learning via Superposition Coding and Successive Decoding

no code implementations5 Dec 2021 Hankyul Baek, Won Joon Yun, Soyi Jung, Jihong Park, Mingyue Ji, Joongheon Kim, Mehdi Bennis

To address the heterogeneous communication throughput problem, each full-width (1. 0x) SNN model and its half-width ($0. 5$x) model are superposition-coded before transmission, and successively decoded after reception as the 0. 5x or $1. 0$x model depending on the channel quality.

Federated Learning

Joint Superposition Coding and Training for Federated Learning over Multi-Width Neural Networks

no code implementations5 Dec 2021 Hankyul Baek, Won Joon Yun, Yunseok Kwak, Soyi Jung, Mingyue Ji, Mehdi Bennis, Jihong Park, Joongheon Kim

By applying SC, SlimFL exchanges the superposition of multiple width configurations that are decoded as many as possible for a given communication throughput.

Federated Learning

Trends in Neural Architecture Search: Towards the Acceleration of Search

no code implementations19 Aug 2021 Youngkee Kim, Won Joon Yun, Youn Kyu Lee, Soyi Jung, Joongheon Kim

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.

Evolutionary Algorithms Neural Architecture Search +2

Joint Pilot Design and Channel Estimation using Deep Residual Learning for Multi-Cell Massive MIMO under Hardware Impairments

no code implementations10 Aug 2021 Byungju Lim, Won Joon Yun, Joongheon Kim, Young-Chai Ko

After that, a deep learning based pilot design is proposed to minimize the mean square error (MSE) of LMMSE channel estimation, which is utilized to the joint pilot design and channel estimator for transfer learning approach.

Transfer Learning

Quantum Neural Networks: Concepts, Applications, and Challenges

no code implementations2 Aug 2021 Yunseok Kwak, Won Joon Yun, Soyi Jung, Joongheon Kim

Quantum deep learning is a research field for the use of quantum computing techniques for training deep neural networks.

Attention-based Reinforcement Learning for Real-Time UAV Semantic Communication

no code implementations22 May 2021 Won Joon Yun, Byungju Lim, Soyi Jung, Young-Chai Ko, Jihong Park, Joongheon Kim, Mehdi Bennis

In this article, we study the problem of air-to-ground ultra-reliable and low-latency communication (URLLC) for a moving ground user.

Graph Attention reinforcement-learning +1

Multi-Agent Deep Reinforcement Learning using Attentive Graph Neural Architectures for Real-Time Strategy Games

no code implementations21 May 2021 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.

Graph Attention Reinforcement Learning (RL) +2

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