most citedIntroduction to Quantum Reinforcement Learning: Theory and PennyLane-based Implementation

8 citations · 14 across the 10 of their papers we have counts for

collaborators

10 papers

eess.SY2021

Stable Marriage Matching for Traffic-Aware Space-Air-Ground Integrated Networks: A Gale-Shapley Algorithmic Approach

Hyunsoo Lee, Haemin Lee, Soyi Jung +1

In keeping with the rapid development of communication technology, a new communication structure is required in a next-generation communication system. In particular, research usin…

cs.LG2021

Trends in Neural Architecture Search: Towards the Acceleration of Search

Youngkee Kim, Won Joon Yun, Youn Kyu Lee +2

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. In this…

cs.LG20218 cited

Introduction to Quantum Reinforcement Learning: Theory and PennyLane-based Implementation

Yunseok Kwak, Won Joon Yun, Soyi Jung +2

The emergence of quantum computing enables for researchers to apply quantum circuit on many existing studies. Utilizing quantum circuit and quantum differential programming, many r…

cs.LG2021

Spatio-Temporal Split Learning

Joongheon Kim, Seunghoon Park, Soyi Jung +1

This paper proposes a novel split learning framework with multiple end-systems in order to realize privacypreserving deep neural network computation. In conventional split learning…

quant-ph20214 cited

Quantum Neural Networks: Concepts, Applications, and Challenges

Yunseok Kwak, Won Joon Yun, Soyi Jung +1

Quantum deep learning is a research field for the use of quantum computing techniques for training deep neural networks. The research topics and directions of deep learning and qua…

eess.SY20212 cited

Quantum Scheduling for Millimeter-Wave Observation Satellite Constellation

Joongheon Kim, Yunseok Kwak, Soyi Jung +1

In beyond 5G and 6G network scenarios, the use of satellites has been actively discussed for extending target monitoring areas, even for extreme circumstances, where the monitoring…