9 citations · 15 across the 5 of their papers we have counts for
5 papers
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…
Projection Valued Measure-based Quantum Machine Learning for Multi-Class Classification
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. However, these QML…
Parallelized and Randomized Adversarial Imitation Learning for Safety-Critical Self-Driving Vehicles
Won Joon Yun, MyungJae Shin, Soyi Jung +2
Self-driving cars and autonomous driving research has been receiving considerable attention as major promising prospects in modern artificial intelligence applications. According t…
Communication and Energy Efficient Slimmable Federated Learning via Superposition Coding and Successive Decoding
Hankyul Baek, Won Joon Yun, Soyi Jung +4
Mobile devices are indispensable sources of big data. Federated learning (FL) has a great potential in exploiting these private data by exchanging locally trained models instead of…
Joint Superposition Coding and Training for Federated Learning over Multi-Width Neural Networks
Hankyul Baek, Won Joon Yun, Yunseok Kwak +5
This paper aims to integrate two synergetic technologies, federated learning (FL) and width-adjustable slimmable neural network (SNN) architectures. FL preserves data privacy by ex…